Imaging analysis tools, a table by Biafra Ahanonu, PhD

Imaging analysis with CIAtah (https://github.com/bahanonu/ciatah ).

With the increased use of calcium (and voltage) imaging for a plethora of research purposes, the need for tools that can accurately, quickly, and efficiently process this data is needed. As a graduate student in Mark Schnitzer's lab , I built and furthered new tools (e.g. CELLMax and CLEAN) and software packages (see CIAtah, https://github.com/bahanonu/ciatah ) to improve analysis of calcium imaging data. While there are existing reviews covering calcium imaging analysis, I decided to expand upon the table in my dissertation to include more recent and additional older algorithms, tools, and analysis pipelines. Those interested in a brief overview of calcium imaging, see the return of the brain initiative notes .

The table below is primarily focused on tools for calcium imaging, but some of them also include tools for voltage imaging, data handling for biology, and more. The goal will be to expand this to include additional imaging analysis tools going forward and I might make it more dynamic akin to my Nobel Prize Browser .

This is a part of the brain initiative notes and can also be found at neuroscience imaging analysis tools or https://github.com/bahanonu/imaging_tools .

Table updates
Below is a changelog of updates to the table, such as adding new methods.

2021.11.14 - Added FIBSI, SpecSeg, FIOLA, and PatchWarp.
2021.11.29 - Added MVG-CNN.
2023.09.12 - Updated online table to include additional papers (added throughout 2022-2023).

Table note

I use cell extraction to refer to algorithms that perform cell segmentation and extract neural activity traces.
Any additional papers or algorithms that should be added or suggested updates to the table, leave a comment below or open an issue on the GitHub page, I want to make sure everyone’s brilliant work is acknowledged!
In cases where the publication did not explicitly give the algorithm a name, made one based on the underlying method used.
This table includes algorithms that simultaneously extract cell images/contours and reconstruct cell activity traces along with ones mainly focused on determining one or the other.
Several calcium imaging related packages have also been included along with algorithms dealing with post-hoc handling of data or cell activity traces.
CELLMax is our algorithm that we have presented at Society for Neuroscience and COSYNE.

Table 1:Ca²⁺ imaging cell extraction and trace reconstruction algorithms


#	Method	Year	Analysis pipeline	Notes/Code	Citation

1	PhaseCorrelation	1996	Motion correction.	• Phase correlation for motion correction, to include translation, rotation, and scale-invariance.	Reddy and Chatterji 1996
2	Turboreg	1998	Motion correction.	• Motion correction. • http://bigwww.epfl.ch/thevenaz/turboreg/	Thevenaz et al. 1998
3	subPixelPhase	2002	Motion correction.	• Closed-form solution to subpixel translation estimation using phase correlation.	Foroosh et al. 2002
4	ROI	2005	Cell extraction	• Matrix multiplication; in some methods neuropil/background subtraction implemented.	Kerr et al. 2005; Kuchibhotla et al. 2014; Peron et al. 2015
5	CellProfiler	2006	Cell segmentation	• Multi-algorithm pipeline for cell segmentation. • https://cellprofiler.org	Carpenter et al. 2006; McQuin et al. 2018; Lamprecht et al. 2007
6	PCA-ICA	2009	Cell extraction	• Cell extraction using principal component analysis (PCA) followed by independent component analysis (ICA).	Mukamel et al. 2009
7	ANTs	2009	Image analysis	• Suite of tools for registering and analyzing imaging data. • http://stnava.github.io/ANTs/	Avants et al. 2009
8	elastix	2009	Motion correction	• A general toolbox for rigid and non-rigid image registration. • https://elastix.lumc.nl	Klein et al. 2009
9	Lucas–Kanade framework	2009	Motion correction	• Lucas-Kanade framework for non-uniform motion image registration.	Greenberg and Kerr 2009
10	CIRF (calcium-behavior)	2011	Cell extraction	• Regressive model to obtain Ca²⁺ signal based on behavior.	Miri et al. 2011
11	openBIS	2011	Data handling	• FAIR data management. • https://openbis.ch	Bauch et al. 2011
12	Automated ROI analysis	2012	Cell extraction	• Automatic ellipses based ROI detection.	Francis et al. 2012
13	OMERO	2012	Data handling	• Microscopy data handling. • https://www.openmicroscopy.org	Allan et al. 2012
14	ADINA	2013	Cell extraction	• Sparse dictionary learning.	Diego et al. 2013
15	TPP	2013	Analysis pipeline	• Tool for processing two-photon calcium imaging data, e.g. finding cells with SeNeCA. • http://uemweb.biomed.cas.cz/tpp/	Tomek et al. 2013
16	NMF	2014	Cell extraction	• Cell extraction using nonnegative matrix factorization (NMF). Followed by CNMF.	Pnevmatikakis et al. 2014; Maruyama et al. 2014
17	SIMA	2014	Analysis pipeline	• Normalized cut segmentation, motion correction, etc. • https://github.com/losonczylab/sima	Kaifosh et al. 2014
18	DataJoint	2015	Data handling	• Schema for data handling. • https://github.com/datajoint/datajoint-matlab	Yatsenko et al. 2015
19	NWB	2015	Data handling	• Neurodata Without Borders (NWB) initiative to produce a common data format for electrophysiology and imaging studies. • https://github.com/NeurodataWithoutBorders	Teeters et al. 2015
20	Suite2p	2016	Cell extraction	• Generative model along with GUIs.	Pachitariu et al. 2016
21	CNMF (CaImAn)	2016	Cell extraction	• Constrained NMF (CNMF). • https://github.com/flatironinstitute/CaImAn-MATLAB	Pnevmatikakis et al. 2016
22	CNMF-E	2016	Cell extraction	• CNMF + background model to handle one-photon data. • https://github.com/zhoupc/CNMF_E	Zhou et al. 2016, 2018
23	Apthorpe CNN	2016	Cell segmentation	• Convolutional neural network (CNN).	Apthorpe et al. 2016
24	moco	2016	Motion correction	• Fourier-transform based motion correction. • https://github.com/NTCColumbia/moco	Dubbs et al. 2016
25	Cytomine	2016	Analysis GUI	• Analysis of large-scale imaging data. • https://cytomine.be	Marée et al. 2016
26	ROI clustering	2016	Cell extraction	• Select high-intensity pixels then perform clustering to segment. • https://www.bu.edu/hanlab/files/2016/02/pfgc.zip	Mohammed et al. 2016
27	CELLMax (conference)	2017	Cell extraction	• Cell segmentation and activity trace extraction using a maximum likelihood approach.	Ahanonu et al. 2018, 2017; Ahanonu 2018
28	sc-CNMF	2017	Cell extraction	• CNMF + GMM/RNN seed cleansing.	Lu et al. 2017
29	OASIS	2017	Trace analysis	• Generalized pool adjacent violators algorithm. • https://github.com/zhoupc/OASIS_matlab	Friedrich et al. 2017
30	ABLE	2017	Cell segmentation	• Multiple active contours and a cost function to identify cells in 2P data. • https://github.com/StephanieRey/ABLE	Reynolds et al. 2017
31	SCALPEL	2017	Cell extraction	• Dictionary learning, dissimilarity, and clustering. • https://cran.r-project.org/web/packages/scalpel/index.html	Petersen et al. 2017
32	HNCcorr	2017	Cell segmentation	• Combinatorial optimization (correlation space analysis). • https://github.com/hochbaumGroup/HNCcorr	Spaen et al. 2017
33	OnACID	2017	Cell extraction (online)	• NMF variant for online Ca²⁺ imaging processing.	Giovannucci et al. 2017
34	EXTRACT	2017	Cell extraction	• Robust statistical estimation.	Inan et al. 2017
35	NETCAL	2017	Analysis pipeline	• Calcium imaging analysis GUI. • https://github.com/orlandi/netcal	Orlandi et al.
36	NoRMCorre	2017	Motion correction.	• Piecewise rigid motion correction. • https://github.com/simonsfoundation/NoRMCorre	Pnevmatikakis and Giovannucci 2017
37	CellReg	2017	Cross-session alignment	• Alignment of cells across days using a probabilistic approach. • https://github.com/zivlab/CellReg	Sheintuch et al. 2017
38	NeuroSeg	2017	Cell segmentation	• Filtering and seed/clustering based cell segmentation. • https://github.com/baidatong/NeuroSeg	Guan et al. 2018
39	CNMF-E+	2017	Cell extraction	• Shrinkage estimation to improve CNMF-E initialization.	Takekawa et al. 2017
40	Toolbox-Romano	2017	Analysis pipeline	• Full analysis pipeline with ROI-based segmentation • https://github.com/zebrain-lab/Toolbox-Romano-et-al	Romano et al. 2017
41	SamuROI	2017	Analysis GUI	• GUI for data visualization • https://github.com/samuroi/SamuROI	Rueckl et al. 2017
42	KNIME	2017	Analysis pipeline	• Workflow manager for data analysis. • https://www.knime.com	Fillbrunn et al. 2017
43	U-Net2DS	2017	Cell segmentation	• Evaluated several deep learning models on Neurofinder, U-Net2DS best. • https://github.com/alexklibisz/deep-calcium	Klibisz et al. 2017
44	CLEAN (conference)	2018	Cell sorting	• Machine learning based cell sorting of cell extraction outputs based on image and activity trace features.	Ahanonu et al. 2018; Ahanonu 2018
45	FISSA	2018	Trace analysis	• Neuropil decontamination using local region around cell. • https://github.com/rochefort-lab/fissa	Keemink et al. 2018
46	LSSC	2018	Cell segmentation	• Spectral clustering; variant to find local subset of eigenvectors.	Mishne et al. 2018
47	PMD - PCA	2018	Denoising	• Spatially-localized penalized matrix decomposition for denoising; compression; and improved demixing. • https://github.com/paninski-lab/funimag	Buchanan et al. 2018
48	MIN1PIPE	2018	Analysis pipeline	• Pre-processing to enhance neural signals then sc-CNMF for cell extraction.	Lu et al. 2018
49	CaImAn (preprint)	2018	Analysis pipeline	• CNMF + several other processing tools.	Giovannucci et al. 2018
50	SEUDO (preprint)	2018	Trace analysis	• Mixture of Gaussians + maximum likelihood; post-hoc activity trace correction.	Gauthier et al. 2018
51	ACSAT	2018	Cell segmentation	• Global and local adaptive thresholding to identify neurons. • https://github.com/sshen8/acsat	Shen et al. 2018
52	onlineMotionCorrection	2018	Motion correction	• Tested multiple algorithms and developed an online motion correction pipeline. • https://github.com/amitani/onlineMotionCorrection	Mitani and Komiyama 2018
53	CIAtah	2019	Analysis pipeline	• 1P and 2P Imaging analysis pipeline supporting PCA-ICA, CNMF, CELLMax, EXTRACT, etc. • https://github.com/bahanonu/ciatah	Corder et al. 2019; Ahanonu 2018; Ahanonu and Corder 2022
54	NAOMi (bioRxiv)	2019	Simulator	• Generative model for creating simulated calcium imaging movies.	Charles et al. 2019
55	CALIMA	2019	Analysis pipeline	• Calcium imaging analysis GUI.	Radstake et al. 2019
56	STNeuroNet	2019	Cell segmentation	• Convolutional neural network to detect and segment cells.	Soltanian-Zadeh et al. 2019
57	AQuA	2019	Cell extraction	• Astrocyte imaging focused. Non-ROI cluster and propagation based detection of events.	Wang et al. 2019
58	CaImAn	2019	Analysis pipeline	• Popular calcium imaging pipeline that includes CNMF + several other processing tools. • https://github.com/flatironinstitute/CaImAn	Giovannucci et al. 2019
59	DL+RWL1-SF	2019	Cell extraction	• Dictionary learning and spatial correlation based cell extraction.	Mishne and Charles 2019
60	Segment2P	2019	Cell segmentation	• Pre-process images and run through DeepLabV3. • https://github.com/NoahDolev/Segment2P	Dolev et al. 2019
61	LANMC	2019	Motion correction	• Long short-term memory non-rigid motion correction, reduce computational cost by predicting non-rigid motion.	Chen et al. 2019
62	marked point processes	2020	Cell extraction	• Probabilistic generative model, specifically a marked point process, to extract activity traces.	Shibue and Komaki 2020
63	LocaNMF	2020	Region extraction	• Localized semi-nonnegative matrix factorization for extracting active regions. • https://github.com/ikinsella/locaNMF	Saxena et al. 2020
64	EZcalcium	2020	Analysis pipeline	• Calcium imaging analysis toolbox. • https://github.com/porteralab/EZcalcium	Cantu et al. 2020
65	OnACID-E + ring CNN	2020	Cell extraction (online)	• OnACID for miniscope and new ring CNN background model to improve accuracy. • https://github.com/flatironinstitute/CaImAn	Friedrich et al. 2020
66	Auto CNMF-E sorting	2020	Cell sorting	• Machine learning (AutoML) based curation of CNMF-E outputs. • https://github.com/jf-lab/cnmfe-reviewer	Tran et al. 2020a,b
67	DeepInterpolation	2020	Denoising	• Encoder-decoder architecture with 2D conv. to denoise imaging data. • https://github.com/AllenInstitute/deepinterpolation	Lecoq et al. 2020
68	BIAFLOWS	2020	Benchmarking	• Framework for benchmarking imaging analysis workflows. • https://biaflows.neubias.org	Rubens et al. 2020
69	FIBSI	2020	Trace analysis	• Extension of Ramer-Douglas-Peucker algorithm to identify baseline that is used for signal detection. • https://github.com/rmcassidy/FIBSI_program	Cassidy et al. 2020; Alles et al. 2021
70	DISCo	2020	Cell segmentation	• Pixel correlation and deep learning (CNN) + graph based segmentation. • https://github.com/EKirschbaum/DISCo	Kirschbaum et al. 2020
71	DeepCINAC	2020	Trace analysis	• Trace analysis after human labeling followed by CNNs + bidirectional long-short term memory (LSTM) network. • https://gitlab.com/cossartlab/deepcinac	Denis et al. 2020
72	NDSEP	2020	Cell extraction	• Dataflow framework for real-time calcium imaging processing. • http://dspcad-www.iacs.umd.edu/bcnm/index.html	Lee et al. 2020
73	DeepBrainSeg	2020	Segmentation	• Dual-pathway CNN to learn local and contextual features.	Tan et al. 2020
74	RT-3DMC	2020	Motion correction	• Bead or soma tracking for real-time motion correction during 2P imaging. • https://github.com/SilverLabUCL/SilverLab-Microscope	Griffiths et al. 2020
75	Cellpose	2021	Cell segmentation	• Neural network and gradient-based cell segmentation. • https://github.com/mouseland/cellpose	Stringer et al. 2021
76	NAOMi	2021	Simulator	• Detailed model simulation for benchmarking calcium imaging algorithms. • https://bitbucket.org/adamshch/naomi_sim/src/master/	Song et al. 2021
77	OnACID-E + ring CNN	2021	Cell extraction (online)	• OnACID for 1P data and ring CNN background model. • https://github.com/flatironinstitute/CaImAn	Friedrich et al. 2021
78	EXTRACT	2021	Cell extraction	• Robust statistics based cell extraction. • https://github.com/schnitzer-lab/EXTRACT-public	Inan et al. 2021
79	Minian	2021	Analysis pipeline	• Imaging analysis pipeline with CNMF for cell extraction, in part using Jupyter notebooks with GUI elements. • https://github.com/DeniseCaiLab/minian	Dong et al. 2021
80	Mesmerize	2021	Analysis pipeline	• Imaging analysis platform with CaImAn for cell extraction, import support for other cell extraction algorithms. • https://github.com/kushalkolar/MESmerize	Kolar et al. 2021
81	DeepInterpolation	2021	Denoising	• Encoder-decoder architecture with 2D conv. to denoise imaging data. • https://github.com/AllenInstitute/deepinterpolation	Lecoq et al. 2021
82	BEAR	2021	Cell extraction	• Neural network approximation of PCA for cell extraction. • https://github.com/NICALab/BEAR	Han et al. 2021
83	CaPTure	2021	Cell extraction	• ROI segmentation and activity extraction. • https://github.com/LieberInstitute/CaPTure	Tippani et al. 2021
84	CASCADE	2021	Trace analysis	• Spike inference based on dual ephys/calcium imaging recordings. • https://github.com/HelmchenLabSoftware/Cascade	Rupprecht et al. 2021
85	VolPy	2021	Analysis pipeline	• Voltage imaging analysis pipeline integrated into CaImAn. • https://github.com/flatironinstitute/CaImAn	Cai et al. 2021
86	DeepCAD	2021	Denoising	• Deep neural network based denoising. • https://github.com/cabooster/DeepCAD-RT	Li et al. 2021
87	SpecSeg	2021	Cell extraction	• Spectral density of pixels to identify ROIs. Also incorporates motion correction and cross-session matching. • https://github.com/Leveltlab/SpectralSegmentation	de Kraker et al. 2021
88	FIOLA	2021	Cell extraction (online)	• GPU- and computational graph-based speed-ups along with non-negative least squares for post-initialization signal extraction. • https://github.com/nel-lab/FIOLA	Giovannucci et al. 2021
89	PatchWarp	2021	Motion correction	• Affine transformation of subfields followed by stitching subfields together. • https://github.com/ryhattori/PatchWarp	Hattori and Komiyama 2021
90	MVG-CNN	2021	Region extraction	• Automated sleep states classification using multiplex visibility graphs and deep learning. Data URL . • https://github.com/comp-imaging-sci/MVG-CNN	Zhang et al. 2021
91	Flow-Registration	2021	Motion correction	• Variational optical flow for non-uniform motion correction • https://github.com/phflot/flow_registration	Flotho et al. 2022
92	SUNS	2021	Cell segmentation	• Cell segmentation using shallow U-Nets. • https://github.com/YijunBao/Shallow-UNet-Neuron-Segmentation_SUNS	Bao et al. 2021
93	Carignan	2021	Cell extraction	• Online cell extraction and triggering based on OnACID and CaImAn. • https://github.com/tzklab/carignan	Taniguchi et al. 2021
94	MullenClassifier	2021	Cell sorting	• Feature extraction from cell images and tracs followed by supervised learning classifier.	Mullen et al. 2021
95	timeUnet	2021	Denoising	• Deep learning for denoising with temporal information added in. • https://github.com/BoHuangLab/Transfer-Learning-Denoising/	Wang et al. 2021
96	EMC²	2021	Motion correction	• Wavelet decomposition to detect bright spots followed by motion correction with multiple hypothesis tracking and computing elastic deformation. • https://icy.bioimageanalysis.org/plugin/elastic-motion-correction-concatenation-emc2-of-tracks/	Lagache et al. 2021
97	GraFT	2022	Cell extraction	• Dictionary-based learning of activity traces followed by graph-based segmentation. • https://github.com/adamshch/GraFT-analysis	Charles et al. 2022
98	CaPTure	2022	Analysis pipeline	• Binary/watershed segmentation followed by ROI-based mean traces. • https://github.com/LieberInstitute/CaPTure	Tippani et al. 2022
99	SpecSeg	2022	Cell segmentation	• Cross spectral power-based segmentation of neurons and neurites. • https://github.com/Leveltlab/SpectralSegmentation	de Kraker et al. 2022
100	CITE-On	2022	Cell extraction	• Online cell detection and trace extraction using CNNs. • https://gitlab.iit.it/fellin-public/cite-on	Sità et al. 2022
101	DL-assisted 2P fiberscope	2022	Denoising	• Denoising 2P fiberscope data using deep neural network (conditional generative adversarial network). • https://figshare.com/articles/dataset/Data/19193792	Guan et al. 2022
102	4SM	2022	Cell extraction	• Generative adversarial network for image segmentation. • https://github.com/SharifAmit/4SM	Kamran et al. 2022
103	DeepCAD-RT	2022	Denoising	• Improved version of DeepCAD for real time performance. • https://github.com/cabooster/DeepCAD-RT/	Li et al. 2023a
104	SEUDO	2022	Trace analysis	• Mixture of Gaussians + maximum likelihood; post-hoc activity trace correction. • https://github.com/adamshch/SEUDO	Gauthier et al. 2022
105	AxialMotionCorrect	2022	Motion correction	• Axial motion correction via multi-plane scanning plus maximum likelihood optimization. • https://gitlab.com/anflores/axial_motion_correction	Flores-Valle and Seelig 2022
106	FIFER	2022	Motion correction	• Feature-based motion correction, finding features using a density-based estimating and clustering algorithm and matching features with a similarity metric for registration. • https://github.com/Weiyi-Liu-Unique/FIFER	Liu et al. 2022
107	NWB	2022	Data handling	• Neurodata Without Borders (NWB) to standardize ephys and imaging data across tools. • https://github.com/NeurodataWithoutBorders	Rübel et al. 2022
108	DeCalciOn	2023	Online analysis pipeline	• Integrate hardware and software to online decode calcium signals. • https://github.com/zhe-ch/ACTEV	Chen et al. 2023
109	jGCaMP8	2023	Calcium indicator	• Improved calcium indicators with increased sensitivity and reduced background.	Zhang et al. 2023a
110	NeuroSeg-II	2023	Cell segmentation	• 2P cell segmentation using region-based convolutional neural network with modifications. • https://github.com/XZH-James/NeuroSeg2	Xu et al. 2023
111	CaliAli	2023	Cross-session alignment	• Cross-session alignment using vasculature information. • https://github.com/CaliAli-PV/CaliAli	Vergara et al. 2023
112	DeepWonder	2023	Cell extraction	• Deep-learning-based cell finding for widefield datasets. • https://github.com/yuanlong-o/Deep_widefield_cal_inferece	Zhang et al. 2023b
113	ASTRA	2023	Cell segmentation	• Deep neural network for astrocyte segmentation. • https://gitlab.iit.it/fellin-public/astra	Bonato et al. 2023
114	SRDTrans	2023	Denoise	• Spatial redundancy for training followed by spatiotemporal transformer architecture to reduce CNN bias/issues. • https://github.com/cabooster/SRDTrans	Li et al. 2023b
115	REALS	2023	Motion correction	• Motion correction via simultaneous transformation and low rank and sparse decomposition with gradient-based updates. • https://openaccess.thecvf.com/content/WACV2023/supplemental/Cho_Robust_and_Efficient_WACV_2023_supplemental.zip	Cho et al. 2023
116	LD-MCM	2023	Motion correction	• Motion correction using deep learning feature identification and control point registration. • https://github.com/bahanonu/ciatah	Ahanonu et al. 2023

References

B Srinivasa Reddy and Biswanath N Chatterji. An fft-based technique for translation, rotation, and scale-invariant image registration. IEEE transactions on image processing, 5(8):1266–1271, 1996.

Philippe Thevenaz, Urs E Ruttimann, and Michael Unser. A pyramid approach to subpixel registration based on intensity. Image Processing, IEEE Transactions on, 7(1):27–41, 1998.

Hassan Foroosh, Josiane B Zerubia, and Marc Berthod. Extension of phase correlation to subpixel registration. IEEE transactions on image processing, 11(3):188–200, 2002.

J N Kerr, D Greenberg, and F Helmchen. Imaging input and output of neocortical networks in vivo. Proc Natl Acad Sci U S A, 102(39): 14063–14068, 2005. ISSN 0027-8424 (Print) 0027-8424. doi: 10.1073/pnas. 0506029102.

K V Kuchibhotla, S Wegmann, K J Kopeikina, J Hawkes, N Rudinskiy, M L Andermann, T L Spires-Jones, B J Bacskai, and B T Hyman. Neurofibrillary tangle-bearing neurons are functionally integrated in cortical circuits in vivo. Proc Natl Acad Sci U S A, 111(1):510–514, 2014. ISSN 0027-8424. doi: 10.1073/pnas.1318807111.

Simon P. Peron, Jeremy Freeman, Vijay Iyer, Caiying Guo, and Karel Svoboda. A Cellular Resolution Map of Barrel Cortex Activity during Tactile Behavior. Neuron, 86(3): 783–799, 2015. ISSN 10974199. doi: 10.1016/j.neuron.2015.03.027. URL http://dx.doi.org/10.1016/j.neuron.2015.03.027.

Anne E Carpenter, Thouis R Jones, Michael R Lamprecht, Colin Clarke, In Han Kang, Ola Friman, David A Guertin, Joo Han Chang, Robert A Lindquist, Jason Moffat, et al. Cellprofiler: image analysis software for identifying and quantifying cell phenotypes. Genome biology, 7(10):1–11, 2006.

Claire McQuin, Allen Goodman, Vasiliy Chernyshev, Lee Kamentsky, Beth A Cimini, Kyle W Karhohs, Minh Doan, Liya Ding, Susanne M Rafelski, Derek Thirstrup, et al. Cellprofiler 3.0: Next-generation image processing for biology. PLoS biology, 16(7):e2005970, 2018.

Michael R Lamprecht, David M Sabatini, and Anne E Carpenter. Cellprofiler™: free, versatile software for automated biological image analysis. Biotechniques, 42(1):71–75, 2007.

Eran A Mukamel, Axel Nimmerjahn, and Mark J Schnitzer. Automated analysis of cellular signals from large-scale calcium imaging data. Neuron, 63(6):747–760, 2009.

Brian B Avants, Nick Tustison, Gang Song, et al. Advanced normalization tools (ants). Insight j, 2(365):1–35, 2009.

Stefan Klein, Marius Staring, Keelin Murphy, Max A Viergever, and Josien PW Pluim. Elastix: a toolbox for intensity-based medical image registration. IEEE transactions on medical imaging, 29(1):196–205, 2009.

David S Greenberg and Jason ND Kerr. Automated correction of fast motion artifacts for two-photon imaging of awake animals. Journal of neuroscience methods, 176(1):1–15, 2009.

A Miri, K Daie, R D Burdine, E Aksay, and D W Tank. Regression-based identification of behavior-encoding neurons during large-scale optical imaging of neural activity at cellular resolution. J Neurophysiol, 105(2):964–980, 2011. ISSN 1522-1598 (Electronic) 0022-3077 (Linking). doi: 10.1152/jn.00702.2010. URL http://www.ncbi.nlm.nih.gov/pubmed/21084686.

Angela Bauch, Izabela Adamczyk, Piotr Buczek, Franz-Josef Elmer, Kaloyan Enimanev, Pawel Glyzewski, Manuel Kohler, Tomasz Pylak, Andreas Quandt, Chandrasekhar Ramakrishnan, et al. openbis: a flexible framework for managing and analyzing complex data in biology research. BMC bioinformatics, 12(1):1–19, 2011.

M Francis, X Qian, C Charbel, J Ledoux, J C Parker, and M S Taylor. Automated region of interest analysis of dynamic Ca(2)+ signals in image sequences. Am J Physiol Cell Physiol, 303(3):C236–43, 2012. ISSN 0363-6143. doi: 10.1152/ajpcell.00016.2012.

Chris Allan, Jean-Marie Burel, Josh Moore, Colin Blackburn, Melissa Linkert, Scott Loynton, Donald MacDonald, William J Moore, Carlos Neves, Andrew Patterson, et al. Omero: flexible, model-driven data management for experimental biology. Nature methods, 9(3):245–253, 2012.

Ferran Diego, Susanne Reichinnek, Martin Both, and Fred A Hamprecht. Automated identification of neuronal activity from calcium imaging by sparse dictionary learning. In Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on, pages 1058–1061. IEEE, 2013.

Jakub Tomek, Ondrej Novak, and Josef Syka. Two-photon processor and seneca: a freely available software package to process data from two-photon calcium imaging at speeds down to several milliseconds per frame. Journal of neurophysiology, 110(1):243–256, 2013.

Eftychios A Pnevmatikakis, Yuanjun Gao, Daniel Soudry, David Pfau, Clay Lacefield, Kira Poskanzer, Randy Bruno, Rafael Yuste, and Liam Paninski. A structured matrix factorization framework for large scale calcium imaging data analysis. arXiv preprint arXiv:1409.2903, 2014.

Ryuichi Maruyama, Kazuma Maeda, Hajime Moroda, Ichiro Kato, Masashi Inoue, Hiroyoshi Miyakawa, and Toru Aonishi. Detecting cells using non-negative matrix factorization on calcium imaging data. Neural Netw, 55:11–19, mar 2014. ISSN 0893-6080. doi: 10.1016/j.neunet.2014. 03.007. URL http://www.ncbi.nlm.nih.gov/pubmed/24705544.

Patrick Kaifosh, Jeffrey D Zaremba, Nathan B Danielson, and Attila Losonczy. SIMA: Python software for analysis of dynamic fluorescence imaging data. Frontiers in neuroinformatics, 8:80, 2014.

Dimitri Yatsenko, Jacob Reimer, Alexander S Ecker, Edgar Y Walker, Fabian Sinz, Philipp Berens, Andreas Hoenselaar, R James Cotton, Athanassios S Siapas, and Andreas S Tolias. Datajoint: managing big scientific data using matlab or python. BioRxiv, page 031658, 2015.

Jeffery L Teeters, Keith Godfrey, Rob Young, Chinh Dang, Claudia Friedsam, Barry Wark, Hiroki Asari, Simon Peron, Nuo Li, and Adrien Peyrache. Neurodata without borders: creating a common data format for neurophysiology. Neuron, 88(4):629–634, 2015.

Marius Pachitariu, Carsen Stringer, Sylvia Schröder, Mario Dipoppa, L Federico Rossi, Matteo Carandini, and Kenneth D Harris. Suite2p: beyond 10,000 neurons with standard two-photon microscopy. Biorxiv, page 061507, 2016.

Eftychios A Pnevmatikakis, Daniel Soudry, Yuanjun Gao, Timothy A Machado, Josh Merel, David Pfau, Thomas Reardon, Yu Mu, Clay Lacefield, Weijian Yang, et al. Simultaneous denoising, deconvolution, and demixing of calcium imaging data. Neuron, 89(2):285–299, 2016.

P Zhou, SL Resendez, GD Stuber, RE Kass, and L Paninski. Efficient and accurate extraction of in vivo calcium signals from microendoscope video data. arXiv preprint arXiv:1605.07266, 2016.

Pengcheng Zhou, Shanna L Resendez, Jose Rodriguez-Romaguera, Jessica C Jimenez, Shay Q Neufeld, Andrea Giovannucci, Johannes Friedrich, Eftychios A Pnevmatikakis, Garret D Stuber, Rene Hen, et al. Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data. ELife, 7:e28728, 2018.

Noah Apthorpe, Alexander Riordan, Robert Aguilar, Jan Homann, Yi Gu, David Tank, and H Sebastian Seung. Automatic neuron detection in calcium imaging data using convolutional networks. In Advances in Neural Information Processing Systems, pages 3270–3278, 2016.

Alexander Dubbs, James Guevara, and Rafael Yuste. moco: Fast motion correction for calcium imaging. Frontiers in neuroinformatics, 10:6, 2016.

Raphaël Marée, Loïc Rollus, Benjamin Stévens, Renaud Hoyoux, Gilles Louppe, Rémy Vandaele, Jean-Michel Begon, Philipp Kainz, Pierre Geurts, and Louis Wehenkel. Collaborative analysis of multi-gigapixel imaging data using cytomine. Bioinformatics, 32(9):1395–1401, 2016.

Ali I Mohammed, Howard J Gritton, Hua-an Tseng, Mark E Bucklin, Zhaojie Yao, and Xue Han. An integrative approach for analyzing hundreds of neurons in task performing mice using wide-field calcium imaging. Scientific reports, 6(1):20986, 2016.

B. Ahanonu, L. J. Kitch, T. H. Kim, M. C. Larkin, E. O. Hamel, J. Lecoq, D. E. Aldarondo, and M. J. Schnitzer. Maximum likelihood and machine learning based methods for automated cell sorting of large-scale neural calcium imaging data. Society for Neuroscience, 2018. URL https://abstractsonline.com/pp8/#!/4649/presentation/41917.

B. Ahanonu, L. J. Kitch, T. H. Kim, M. C. Larkin, E. O. Hamel, J. Lecoq, and M. J. Schnitzer. Maximum likelihood based cell sorting of large-scale neural calcium imaging data. Society for Neuroscience, 2017. URL http://www.abstractsonline.com/pp8/index.html#!/4376/presentation/18520.

Biafra Owowonta Ahanonu. Neural Ensemble Dynamics in Behaving Animals: Computational Approaches and Applications in Amygdala and Striatum. Stanford University, 2018.

Jinghao Lu, Chunyuan Li, and Fan Wang. Seeds cleansing cnmf for spatiotemporal neural signals extraction of miniscope imaging data. arXiv preprint arXiv:1704.00793, 2017.

Johannes Friedrich, Pengcheng Zhou, and Liam Paninski. Fast online deconvolution of calcium imaging data. PLoS computational biology, 13 (3):e1005423, 2017.

Stephanie Reynolds, Therese Abrahamsson, Renaud Schuck, P Jesper Sjöström, Simon R Schultz, and Pier Luigi Dragotti. Able: An activity-based level set segmentation algorithm for two-photon calcium imaging data. eNeuro, pages ENEURO–0012, 2017.

Ashley Petersen, Noah Simon, and Daniela Witten. SCALPEL: Extracting Neurons from Calcium Imaging Data. ArXiv e-prints, art. arXiv:1703.06946, March 2017.

Quico Spaen, Dorit S Hochbaum, and Roberto Asín-Achá. Hnccorr: A novel combinatorial approach for cell identification in calcium-imaging movies. arXiv preprint arXiv:1703.01999, 2017.

Andrea Giovannucci, Johannes Friedrich, Matt Kaufman, Anne Churchland, Dmitri Chklovskii, Liam Paninski, and Eftychios A Pnevmatikakis. Onacid: Online analysis of calcium imaging data in real time. In Advances in Neural Information Processing Systems, pages 2381–2391, 2017.

Hakan Inan, Murat A Erdogdu, and Mark Schnitzer. Robust estimation of neural signals in calcium imaging. In Advances in Neural Information Processing Systems, pages 2901–2910, 2017.

JG Orlandi, S Fernández-García, A Comella-Bolla, M Masana, G García-Díaz Barriga, M Yaghoubi, A Kipp, JM Canals, MA Colicos, J Davidsen, et al. Netcal: An interactive platform for large-scale, network and population dynamics analysis of calcium imaging recordings, zenodo (2017).

Eftychios A Pnevmatikakis and Andrea Giovannucci. Normcorre: An online algorithm for piecewise rigid motion correction of calcium imaging data. Journal of neuroscience methods, 291:83–94, 2017.

Liron Sheintuch, Alon Rubin, Noa Brande-Eilat, Nitzan Geva, Noa Sadeh, Or Pinchasof, and Yaniv Ziv. Tracking the same neurons across multiple days in ca2+ imaging data. Cell reports, 21(4):1102–1115, 2017.

Jiangheng Guan, Jingcheng Li, Shanshan Liang, Ruijie Li, Xingyi Li, Xiaozhe Shi, Ciyu Huang, Jianxiong Zhang, Junxia Pan, Hongbo Jia, et al. Neuroseg: automated cell detection and segmentation for in vivo two-photon ca 2+ imaging data. Brain Structure and Function, 223(1): 519–533, 2018.

Takashi Takekawa, Hirotaka Asai, Noriaki Ohkawa, Masanori Nomoto, Reiko Okubo-Suzuki, Khaled Ghandour, Masaaki Sato, Yasunori Hayashi, Kaoru Inokuchi, and Tomoki Fukai. Automatic sorting system for large calcium imaging data. bioRxiv, page 215145, 2017.

Sebastián A Romano, Verónica Pérez-Schuster, Adrien Jouary, Jonathan Boulanger-Weill, Alessia Candeo, Thomas Pietri, and Germán Sumbre. An integrated calcium imaging processing toolbox for the analysis of neuronal population dynamics. PLoS computational biology, 13(6): e1005526, 2017.

Martin Rueckl, Stephen C Lenzi, Laura Moreno-Velasquez, Daniel Parthier, Dietmar Schmitz, Sten Ruediger, and Friedrich W Johenning. Samuroi, a python-based software tool for visualization and analysis of dynamic time series imaging at multiple spatial scales. Frontiers in neuroinformatics, 11:44, 2017.

Alexander Fillbrunn, Christian Dietz, Julianus Pfeuffer, René Rahn, Gregory A Landrum, and Michael R Berthold. Knime for reproducible cross-domain analysis of life science data. Journal of biotechnology, 261: 149–156, 2017.

Aleksander Klibisz, Derek Rose, Matthew Eicholtz, Jay Blundon, and Stanislav Zakharenko. Fast, simple calcium imaging segmentation with fully convolutional networks. In International Workshop on Deep Learning in Medical Image Analysis, pages 285–293. Springer, 2017.

Sander W Keemink, Scott C Lowe, Janelle MP Pakan, Evelyn Dylda, Mark CW Van Rossum, and Nathalie L Rochefort. Fissa: A neuropil decontamination toolbox for calcium imaging signals. Scientific reports, 8 (1):1–12, 2018.

Gal Mishne, Ronald R Coifman, Maria Lavzin, and Jackie Schiller. Automated cellular structure extraction in biological images with applications to calcium imaging data. bioRxiv, page 313981, 2018.

E Kelly Buchanan, Ian Kinsella, Ding Zhou, Rong Zhu, Pengcheng Zhou, Felipe Gerhard, John Ferrante, Ying Ma, Sharon Kim, Mohammed Shaik, et al. Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data. bioRxiv, page 334706, 2018.

Jinghao Lu, Chunyuan Li, Jonnathan Singh-Alvarado, Zhe Charles Zhou, Flavio Fröhlich, Richard Mooney, and Fan Wang. MIN1PIPE: A Miniscope 1-Photon-Based Calcium Imaging Signal Extraction Pipeline. Cell Reports, 23(12):3673–3684, 2018. ISSN 2211-1247.

Andrea Giovannucci, Johannes Friedrich, Pat Gunn, Jeremie Kalfon, Sue Ann Koay, Jiannis Taxidis, Farzaneh Najafi, Jeffrey L Gauthier, Pengcheng Zhou, and David W Tank. CaImAn: An open source tool for scalable Calcium Imaging data Analysis. bioRxiv, page 339564, 2018.

Jeffrey L Gauthier, Sue Ann Koay, Edward H Nieh, David W Tank, Jonathan W Pillow, and Adam S Charles. Detecting and correcting false transients in calcium imaging. bioRxiv, page 473470, 2018.

Simon P Shen, Hua-an Tseng, Kyle R Hansen, Ruofan Wu, Howard J Gritton, Jennie Si, and Xue Han. Automatic cell segmentation by adaptive thresholding (acsat) for large-scale calcium imaging datasets. eneuro, 5(5), 2018.

Akinori Mitani and Takaki Komiyama. Real-time processing of two-photon calcium imaging data including lateral motion artifact correction. Frontiers in neuroinformatics, 12:98, 2018.

Gregory Corder, Biafra Ahanonu, Benjamin F Grewe, Dong Wang, Mark J Schnitzer, and Grégory Scherrer. An amygdalar neural ensemble that encodes the unpleasantness of pain. Science, 363(6424):276–281, 2019.

Biafra Ahanonu and Gregory Corder. Recording pain-related brain activity in behaving animals using calcium imaging calcium imaging and miniature microscopes. In Contemporary Approaches to the Study of Pain: From Molecules to Neural Networks, pages 217–276. Springer, 2022.

Adam S Charles, Alex Song, Jeffrey L Gauthier, Jonathan W Pillow, and David W Tank. Neural anatomy and optical microscopy (naomi) simulation for evaluating calcium imaging methods. bioRxiv, page 726174, 2019.

FDW Radstake, EAL Raaijmakers, R Luttge, Svitlana Zinger, and Jean-Philippe Frimat. Calima: The semi-automated open-source calcium imaging analyzer. Computer methods and programs in biomedicine, 179: 104991, 2019.

Somayyeh Soltanian-Zadeh, Kaan Sahingur, Sarah Blau, Yiyang Gong, and Sina Farsiu. Fast and robust active neuron segmentation in two-photon calcium imaging using spatiotemporal deep learning. Proceedings of the National Academy of Sciences, 116(17):8554–8563, 2019.

Yizhi Wang, Nicole V DelRosso, Trisha V Vaidyanathan, Michelle K Cahill, Michael E Reitman, Silvia Pittolo, Xuelong Mi, Guoqiang Yu, and Kira E Poskanzer. Accurate quantification of astrocyte and neurotransmitter fluorescence dynamics for single-cell and population-level physiology. Nature Neuroscience, 22(11):1936–1944, 2019.

Andrea Giovannucci, Johannes Friedrich, Pat Gunn, Jeremie Kalfon, Brandon L Brown, Sue Ann Koay, Jiannis Taxidis, Farzaneh Najafi, Jeffrey L Gauthier, Pengcheng Zhou, et al. Caiman an open source tool for scalable calcium imaging data analysis. Elife, 8:e38173, 2019.

Gal Mishne and Adam S Charles. Learning spatially-correlated temporal dictionaries for calcium imaging. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 1065–1069. IEEE, 2019.

Noah Dolev, Lior Pinkus, and Michal Rivlin-Etzion. Segment2p: Parameter-free automated segmentation of cellular fluorescent signals. BioRxiv, page 832188, 2019.

Zhe Chen, Hugh T Blair, and Jason Cong. Lanmc: Lstm-assisted non-rigid motion correction on fpga for calcium image stabilization. In Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, pages 104–109, 2019.

Ryohei Shibue and Fumiyasu Komaki. Deconvolution of calcium imaging data using marked point processes. PLoS computational biology, 16(3): e1007650, 2020.

Shreya Saxena, Ian Kinsella, Simon Musall, Sharon H Kim, Jozsef Meszaros, David N Thibodeaux, Carla Kim, John Cunningham, Elizabeth MC Hillman, Anne Churchland, et al. Localized semi-nonnegative matrix factorization (locanmf) of widefield calcium imaging data. PLOS Computational Biology, 16(4):e1007791, 2020.

Daniel A Cantu, Bo Wang, Michael W Gongwer, Cynthia X He, Anubhuti Goel, Anand Suresh, Nazim Kourdougli, Erica D Arroyo, William Zeiger, and Carlos Portera-Cailliau. Ezcalcium: Open source toolbox for analysis of calcium imaging data. bioRxiv, 2020.

Johannes Friedrich, Andrea Giovannucci, and Eftychios A Pnevmatikakis. Online analysis of microendoscopic 1-photon calcium imaging data streams. bioRxiv, 2020.

Lina M Tran, Andrew J Mocle, Adam I Ramsaran, Alex D Jacob, Paul W Frankland, and Sheena A Josselyn. Automated curation of cnmf-e-extracted roi spatial footprints and calcium traces using open-source automl tools. bioRxiv, 2020a.

Lina M Tran, Andrew J Mocle, Adam I Ramsaran, Alexander D Jacob, Paul W Frankland, and Sheena A Josselyn. Automated curation of cnmf-e-extracted roi spatial footprints and calcium traces using open-source automl tools. Frontiers in Neural Circuits, 14:42, 2020b.

Jerome Lecoq, Michael Oliver, Joshua H Siegle, Natalia Orlova, and Christof Koch. Removing independent noise in systems neuroscience data using deepinterpolation. bioRxiv, 2020.

Ulysse Rubens, Romain Mormont, Lassi Paavolainen, Volker Bäcker, Benjamin Pavie, Leandro A Scholz, Gino Michiels, Martin Maška, Devrim Ünay, Graeme Ball, et al. Biaflows: A collaborative framework to reproducibly deploy and benchmark bioimage analysis workflows. Patterns, 1(3):100040, 2020.

Ryan M Cassidy, Alexis G Bavencoffe, Elia R Lopez, Sai S Cheruvu, Edgar T Walters, Rosa A Uribe, Anne Marie Krachler, and Max A Odem. Frequency-independent biological signal identification (fibsi): A free program that simplifies intensive analysis of non-stationary time series data. bioRxiv, 2020.

Sascha RA Alles, Max A Odem, Van B Lu, Ryan M Cassidy, and Peter A Smith. Chronic bdnf simultaneously inhibits and unmasks superficial dorsal horn neuronal activity. Scientific reports, 11(1):1–14, 2021.

Elke Kirschbaum, Alberto Bailoni, and Fred A Hamprecht. Disco: deep learning, instance segmentation, and correlations for cell segmentation in calcium imaging. In Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part V 23, pages 151–162. Springer, 2020.

Julien Denis, Robin F Dard, Eleonora Quiroli, Rosa Cossart, and Michel A Picardo. Deepcinac: a deep-learning-based python toolbox for inferring calcium imaging neuronal activity based on movie visualization. eneuro, 7(4), 2020.

Yaesop Lee, Jing Xie, Eungjoo Lee, Srijesh Sudarsanan, Da-Ting Lin, Rong Chen, and Shuvra S Bhattacharyya. Real-time neuron detection and neural signal extraction platform for miniature calcium imaging. Frontiers in Computational Neuroscience, 14:43, 2020.

Chaozhen Tan, Yue Guan, Zhao Feng, Hong Ni, Zoutao Zhang, Zhiguang Wang, Xiangning Li, Jing Yuan, Hui Gong, Qingming Luo, et al. Deepbrainseg: Automated brain region segmentation for micro-optical images with a convolutional neural network. Frontiers in neuroscience, 14: 179, 2020.

Victoria A Griffiths, Antoine M Valera, Joanna YN Lau, Hana Roš, Thomas J Younts, Bóris Marin, Chiara Baragli, Diccon Coyle, Geoffrey J Evans, George Konstantinou, et al. Real-time 3d movement correction for two-photon imaging in behaving animals. Nature methods, 17(7):741–748, 2020.

Carsen Stringer, Tim Wang, Michalis Michaelos, and Marius Pachitariu. Cellpose: a generalist algorithm for cellular segmentation. Nature Methods, 18(1):100–106, 2021.

Alexander Song, Jeff L Gauthier, Jonathan W Pillow, David W Tank, and Adam S Charles. Neural anatomy and optical microscopy (naomi) simulation for evaluating calcium imaging methods. Journal of Neuroscience Methods, 358:109173, 2021.

Johannes Friedrich, Andrea Giovannucci, and Eftychios A Pnevmatikakis. Online analysis of microendoscopic 1-photon calcium imaging data streams. PLoS computational biology, 17(1):e1008565, 2021.

Hakan Inan, Claudia Schmuckermair, Tugce Tasci, Biafra Ahanonu, Oscar Hernandez, Jérôme Lecoq, Fatih Dinç, Mark J Wagner, Murat Erdogdu, and Mark J Schnitzer. Fast and statistically robust cell extraction from large-scale neural calcium imaging datasets. bioRxiv, 2021.

Zhe Dong, William Mau, Yu Susie Feng, Zachary T Pennington, Lingxuan Chen, Yosif Zaki, Kanaka Rajan, Tristan Shuman, Daniel Aharoni, and Denise J Cai. Minian: An open-source miniscope analysis pipeline. bioRxiv, 2021.

Kushal Kolar, Daniel Dondorp, Jordi Cornelis Zwiggelaar, Jørgen Høyer, and Marios Chatzigeorgiou. Mesmerize: a dynamically adaptable user-friendly analysis platform for 2d & 3d calcium imaging data. bioRxiv, page 840488, 2021.

Jérôme Lecoq, Michael Oliver, Joshua H Siegle, Natalia Orlova, Peter Ledochowitsch, and Christof Koch. Removing independent noise in systems neuroscience data using deepinterpolation. Nature Methods, pages 1–8, 2021.

Seungjae Han, Eun-Seo Cho, Inkyu Park, Kijung Shin, and Young-Gyu Yoon. Efficient neural network approximation of robust pca for automated analysis of calcium imaging data. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 595–604. Springer, 2021.

Madhavi Tippani, Elizabeth A Pattie, Brittany A Davis, Claudia V Nguyen, Yanhong Wang, Srinidhi Rao Sripathy, Brady J Maher, Keri Martinowich, Andrew E Jaffe, and Stephanie Cerceo Page. Capture: Calcium peak toolbox for analysis of in vitro calcium imaging data. bioRxiv, 2021.

Peter Rupprecht, Stefano Carta, Adrian Hoffmann, Mayumi Echizen, Antonin Blot, Alex C Kwan, Yang Dan, Sonja B Hofer, Kazuo Kitamura, Fritjof Helmchen, et al. A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging. Nature Neuroscience, 24(9):1324–1337, 2021.

Changjia Cai, Johannes Friedrich, Amrita Singh, M Hossein Eybposh, Eftychios A Pnevmatikakis, Kaspar Podgorski, and Andrea Giovannucci. Volpy: automated and scalable analysis pipelines for voltage imaging datasets. PLoS computational biology, 17(4):e1008806, 2021.

Xinyang Li, Guoxun Zhang, Jiamin Wu, Yuanlong Zhang, Zhifeng Zhao, Xing Lin, Hui Qiao, Hao Xie, Haoqian Wang, Lu Fang, et al. Reinforcing neuron extraction and spike inference in calcium imaging using deep self-supervised denoising. Nature Methods, pages 1–6, 2021.

Leander de Kraker, Koen Seignette, Premnath Thamizharasu, Bastijn JG van den Boom, Ildefonso Ferreira Pica, Ingo Willuhn, Christiaan N Levelt, and Chris van der Togt. Specseg: cross spectral power-based segmentation of neurons and neurites in chronic calcium imaging datasets. bioRxiv, pages 2020–10, 2021.

Andrea Giovannucci, Changjia Cai, Cynthia Dong, Marton Rozsa, and Eftychios Pnevmatikakis. Fiola: An accelerated pipeline for fluorescence imaging online analysis. 2021.

Ryoma Hattori and Takaki Komiyama. Patchwarp: Corrections of non-uniform image distortions in two-photon calcium imaging data by patchwork affine transformations. bioRxiv, 2021. doi: 10.1101/2021.11.10.468164. URL https://www.biorxiv.org/content/early/2021/11/13/2021.11.10.468164.

Xiaohui Zhang, Eric C Landsness, Wei Chen, Hanyang Miao, Michelle Tang, Lindsey M Brier, Joseph P Culver, Jin-Moo Lee, and Mark A Anastasio. Automated sleep state classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning. Journal of Neuroscience Methods, page 109421, 2021.

Philipp Flotho, Shinobu Nomura, Bernd Kuhn, and Daniel J Strauss. Software for non-parametric image registration of 2-photon imaging data. Journal of Biophotonics, 15(8):e202100330, 2022.

Yijun Bao, Somayyeh Soltanian-Zadeh, Sina Farsiu, and Yiyang Gong. Segmentation of neurons from fluorescence calcium recordings beyond real time. Nature machine intelligence, 3(7):590–600, 2021.

Masaki Taniguchi, Taro Tezuka, Pablo Vergara, Sakthivel Srinivasan, Takuma Hosokawa, Yoan Chérasse, Toshie Naoi, Takeshi Sakurai, and Masanori Sakaguchi. Open-source software for real-time calcium imaging and synchronized neuron firing detection. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pages 2997–3003. IEEE, 2021.

Brian R Mullen, Sydney C Weiser, Desiderio Ascencio, and James B Ackman. Automated classification of signal sources in mesoscale calcium imaging. bioRxiv, pages 2021–02, 2021.

Yina Wang, Henry Pinkard, Emaad Khwaja, Shuqin Zhou, Laura Waller, and Bo Huang. Image denoising for fluorescence microscopy by self-supervised transfer learning. bioRxiv, pages 2021–02, 2021.

Thibault Lagache, Alison Hanson, Jesús E Pérez-Ortega, Adrienne Fairhall, and Rafael Yuste. Tracking calcium dynamics from individual neurons in behaving animals. PLOS Computational Biology, 17(10): e1009432, 2021.

Adam S Charles, Nathan Cermak, Rifqi O Affan, Benjamin B Scott, Jackie Schiller, and Gal Mishne. Graft: graph filtered temporal dictionary learning for functional neural imaging. IEEE Transactions on Image Processing, 31:3509–3524, 2022.

Madhavi Tippani, Elizabeth A Pattie, Brittany A Davis, Claudia V Nguyen, Yanhong Wang, Srinidhi Rao Sripathy, Brady J Maher, Keri Martinowich, Andrew E Jaffe, and Stephanie Cerceo Page. Capture: Calcium peaktoolbox for analysis of in vitro calcium imaging data. BMC neuroscience, 23(1):71, 2022.

Leander de Kraker, Koen Seignette, Premnath Thamizharasu, Bastijn JG van den Boom, Ildefonso Ferreira Pica, Ingo Willuhn, Christiaan N Levelt, and Chris van der Togt. Specseg is a versatile toolbox that segments neurons and neurites in chronic calcium imaging datasets based on low-frequency cross-spectral power. Cell reports methods, 2(10), 2022.

Luca Sità, Marco Brondi, Pedro Lagomarsino de Leon Roig, Sebastiano Curreli, Mariangela Panniello, Dania Vecchia, and Tommaso Fellin. A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging. Nature Communications, 13(1): 1529, 2022.

Honghua Guan, Dawei Li, Hyeon-cheol Park, Ang Li, Yuanlei Yue, Yung-Tian A Gau, Ming-Jun Li, Dwight E Bergles, Hui Lu, and Xingde Li. Deep-learning two-photon fiberscopy for video-rate brain imaging in freely-behaving mice. Nature communications, 13(1):1534, 2022.

Sharif Amit Kamran, Khondker Fariha Hossain, Hussein Moghnieh, Sarah Riar, Allison Bartlett, Alireza Tavakkoli, Kenton M Sanders, and Salah A Baker. New open-source software for subcellular segmentation and analysis of spatiotemporal fluorescence signals using deep learning. Iscience, 25(5), 2022.

Xinyang Li, Yixin Li, Yiliang Zhou, Jiamin Wu, Zhifeng Zhao, Jiaqi Fan, Fei Deng, Zhaofa Wu, Guihua Xiao, Jing He, et al. Real-time denoising enables high-sensitivity fluorescence time-lapse imaging beyond the shot-noise limit. Nature Biotechnology, 41(2):282–292, 2023a.

Jeffrey L Gauthier, Sue Ann Koay, Edward H Nieh, David W Tank, Jonathan W Pillow, and Adam S Charles. Detecting and correcting false transients in calcium imaging. Nature Methods, 19(4):470–478, 2022.

Andres Flores-Valle and Johannes D Seelig. Axial motion estimation and correction for simultaneous multi-plane two-photon calcium imaging. Biomedical Optics Express, 13(4):2035–2049, 2022.

Weiyi Liu, Junxia Pan, Yuanxu Xu, Meng Wang, Hongbo Jia, Kuan Zhang, Xiaowei Chen, Xingyi Li, and Xiang Liao. Fast and accurate motion correction for two-photon ca2+ imaging in behaving mice. Frontiers in Neuroinformatics, 16:851188, 2022.

Oliver Rübel, Andrew Tritt, Ryan Ly, Benjamin K Dichter, Satrajit Ghosh, Lawrence Niu, Pamela Baker, Ivan Soltesz, Lydia Ng, Karel Svoboda, et al. The neurodata without borders ecosystem for neurophysiological data science. Elife, 11:e78362, 2022.

Zhe Chen, Garrett J Blair, Changliang Guo, Jim Zhou, Juan-Luis Romero-Sosa, Alicia Izquierdo, Peyman Golshani, Jason Cong, Daniel Aharoni, and Hugh T Blair. A hardware system for real-time decoding of in vivo calcium imaging data. Elife, 12:e78344, 2023.

Yan Zhang, Márton Rózsa, Yajie Liang, Daniel Bushey, Ziqiang Wei, Jihong Zheng, Daniel Reep, Gerard Joey Broussard, Arthur Tsang, Getahun Tsegaye, et al. Fast and sensitive gcamp calcium indicators for imaging neural populations. Nature, 615(7954):884–891, 2023a.

Zhehao Xu, Yukun Wu, Jiangheng Guan, Shanshan Liang, Junxia Pan, Meng Wang, Qianshuo Hu, Hongbo Jia, Xiaowei Chen, and Xiang Liao. Neuroseg-ii: A deep learning approach for generalized neuron segmentation in two-photon ca2+ imaging. Frontiers in Cellular Neuroscience, 17: 1127847, 2023.

Pablo Vergara, Yuteng Wang, Sakthivel Srinivasan, Yoan Cherasse, Toshie Naoi, Yuki Sugaya, Takeshi Sakurai, Masanobu Kano, and Masanori Sakaguchi. The caliali tool for long-term tracking of neuronal population dynamics in calcium imaging. bioRxiv, pages 2023–05, 2023.

Yuanlong Zhang, Guoxun Zhang, Xiaofei Han, Jiamin Wu, Ziwei Li, Xinyang Li, Guihua Xiao, Hao Xie, Lu Fang, and Qionghai Dai. Rapid detection of neurons in widefield calcium imaging datasets after training with synthetic data. Nature Methods, 20(5):747–754, 2023b.

Jacopo Bonato, Sebastiano Curreli, Sara Romanzi, Stefano Panzeri, and Tommaso Fellin. Astra: a deep learning algorithm for fast semantic segmentation of large-scale astrocytic networks. bioRxiv, pages 2023–05, 2023.

Xinyang Li, Xiaowan Hu, Xingye Chen, Jiaqi Fan, Zhifeng Zhao, Jiamin Wu, Haoqian Wang, and Qionghai Dai. Spatial redundancy transformer for self-supervised fluorescence image denoising. bioRxiv, pages 2023–06, 2023b.

Junmo Cho, Seungjae Han, Eun-Seo Cho, Kijung Shin, and Young-Gyu Yoon. Robust and efficient alignment of calcium imaging data through simultaneous low rank and sparse decomposition. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pages 1939–1948, 2023.

Biafra Ahanonu, Andrew Crowther, Artur Kania, Mariela Rosa Casillas, and Allan Basbaum. Long-term optical imaging of the spinal cord in awake, behaving animals. bioRxiv, pages 2023–05, 2023.

Imaging analysis tools

Biafra Ahanonu, PhD

Methods for calcium imaging cell identification and fluorescence activity trace reconstruction

References

Footnotes