21.4.4.8 Extraction and Analysis of Neurons

Chapter Contents (Back)
Neurons.

Belson, M., Dudley, Jr., A.W., Ledley, R.S.,
Automatic Computer Measurements of Neurons,
PR(1), No. 2, November 1968, pp. 119-128.
Elsevier DOI 0309
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Li, Z.N.[Ze-Nian], Uhr, L.[Leonard],
A pyramidal approach for the recognition of neurons using key features,
PR(19), No. 1, 1986, pp. 55-62.
Elsevier DOI 0309
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Fok, Y.L.[Ying-Lun], Chan, J.C.K., Chin, R.T.,
Automated analysis of nerve-cell images using active contour models,
MedImg(15), No. 3, June 1996, pp. 353-368.
IEEE Top Reference. 0203
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Phillips, J.W., Leahy, R.M., Mosher, J.C.,
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MedImg(16), No. 3, June 1997, pp. 338-348.
IEEE Top Reference. 0205
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IP(11), No. 7, July 2002, pp. 790-801.
IEEE DOI 0207
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Ruthazer, E.S.[Edward S.], Cline, H.T.[Hollis T.],
Multiphoton Imaging of Neurons in Living Tissue: Acquisition and Analysis of Time-Lapse Morphological Data,
RealTimeImg(8), No. 3, June 2002, pp. 175-188.
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Ortiz, F., Torres, F., de Juan, E., Cuenca, N.,
Colour Mathematical Morphology for Neural Image Analysis,
RealTimeImg(8), No. 6, December 2002, pp. 455-465.
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Fudenberg, G., Paninski, L.,
Bayesian Image Recovery for Dendritic Structures Under Low Signal-to-Noise Conditions,
IP(18), No. 3, March 2009, pp. 471-482.
IEEE DOI 0903
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Li, Q., Deng, Z., Zhang, Y., Zhou, X., Valentin Nagerl, U., Wong, S.T.C.,
A Global Spatial Similarity Optimization Scheme to Track Large Numbers of Dendritic Spines in Time-Lapse Confocal Microscopy,
MedImg(30), No. 3, March 2011, pp. 632-641.
IEEE DOI 1103
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Salimi-Khorshidi, G., Nichols, T.E., Smith, S.M., Woolrich, M.W.,
Using Gaussian-Process Regression for Meta-Analytic Neuroimaging Inference Based on Sparse Observations,
MedImg(30), No. 7, July 2011, pp. 1401-1416.
IEEE DOI 1107
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Akselrod-Ballin, A., Bock, D., Reid, R.C., Warfield, S.K.,
Accelerating Image Registration With the Johnson-Lindenstrauss Lemma: Application to Imaging 3-D Neural Ultrastructure With Electron Microscopy,
MedImg(30), No. 7, July 2011, pp. 1427-1438.
IEEE DOI 1107
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Li, Q., Deng, Z.,
A Surface-Based 3-D Dendritic Spine Detection Approach From Confocal Microscopy Images,
IP(21), No. 3, March 2012, pp. 1223-1230.
IEEE DOI 1203
Neural biology. BibRef

Pereira, F.[Francisco], Botvinick, M.[Matthew], Detre, G.[Greg],
Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments,
AI(194), No. 1, January 2013, pp. 240-252.
Elsevier DOI 1211
10.1016/j.artint.2012.06.005. Wikipedia; Matrix factorization; fMRI; Semantic features BibRef

Zhang, M.[Myron], Sakaie, K.E.[Ken E.], Jones, S.E.[Stephen E.],
Logical Foundations and Fast Implementation of Probabilistic Tractography,
MedImg(32), No. 8, 2013, pp. 1397-1410.
IEEE DOI 1307
BibRef
Earlier:
Toward whole-brain maps of neural connections: Logical framework and fast implementation,
MMBIA12(193-197).
IEEE DOI 1203
Connectivity analysis BibRef

Becker, C., Ali, K., Knott, G., Fua, P.,
Learning Context Cues for Synapse Segmentation,
MedImg(32), No. 10, 2013, pp. 1864-1877.
IEEE DOI 1311
bioelectric potentials BibRef

Trapp, M., Schulze, F., Bühler, K., Liu, T., Dickson, B.J.,
3D object retrieval in an atlas of neuronal structures,
VC(29), No. 12, December 2013, pp. 1363-1373.
WWW Link. 1312
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Juan, E.J.[Eduardo J.], González, R.[Rafael], Albors, G.[Gabriel], Ward, M.P.[Matthew P.], Irazoqui, P.[Pedro],
Vagus nerve modulation using focused pulsed ultrasound: Potential applications and preliminary observations in a rat,
IJIST(24), No. 1, 2014, pp. 67-71.
DOI Link 1403
acoustic neuromodulation BibRef

Jagadeesh, V.[Vignesh], Anderson, J.[James], Jones, B.[Bryan], Marc, R.[Robert], Fisher, S.[Steven], Manjunath, B.S.,
Synapse classification and localization in Electron Micrographs,
PRL(43), No. 1, 2014, pp. 17-24.
Elsevier DOI 1404
Connectomics BibRef

Mukherjee, S., Condron, B., Acton, S.T.,
Tubularity Flow Field: A Technique for Automatic Neuron Segmentation,
IP(24), No. 1, January 2015, pp. 374-389.
IEEE DOI 1502
biomedical optical imaging BibRef

Weng, D., Wang, Y., Gong, M., Tao, D., Wei, H., Huang, D.,
DERF: Distinctive Efficient Robust Features From the Biological Modeling of the P Ganglion Cells,
IP(24), No. 8, August 2015, pp. 2287-2302.
IEEE DOI 1505
Computational modeling BibRef

Mata, G.[Gadea], Morales, M.[Miguel], Romero, A.[Ana], Rubio, J.[Julio],
Zigzag persistent homology for processing neuronal images,
PRL(62), No. 1, 2015, pp. 55-60.
Elsevier DOI 1507
Neural images BibRef

Wu, Y.J.[Ying-Jiang], Liu, B.Y.[Ben-Yong],
Spatial and Anatomical Regularization Based on Multiple Kernel Learning for Neuroimaging Classification,
IEICE(E99-D), No. 4, April 2016, pp. 1272-1274.
WWW Link. 1604
BibRef

Wu, Y.J.[Ying-Jiang], Liu, B.Y.[Ben-Yong],
Tensorial Kernel Based on Spatial Structure Information for Neuroimaging Classification,
IEICE(E100-D), No. 6, June 2017, pp. 1380-1383.
WWW Link. 1706
BibRef

Basu, S.[Sreetama], Ooi, W.T., Racoceanu, D.[Daniel],
Neurite Tracing With Object Process,
MedImg(35), No. 6, June 2016, pp. 1443-1451.
IEEE DOI 1606
BibRef
Earlier: A1, A3, Only:
Reconstructing neuronal morphology from microscopy stacks using fast marching,
ICIP14(3597-3601)
IEEE DOI 1502
Image reconstruction BibRef

Li, Z.Y.[Zhong-Yu], Fang, R.[Ruogu], Shen, F.M.[Fu-Min], Katouzian, A.[Amin], Zhang, S.T.[Shao-Ting],
Indexing and mining large-scale neuron databases using maximum inner product search,
PR(63), No. 1, 2017, pp. 680-688.
Elsevier DOI 1612
Neuron morphology BibRef

He, X.X.[Xiao-Xu], Lum, A.[Andrea], Sharma, M.[Manas], Brahm, G.[Gary], Mercado, A.[Ashley], Li, S.[Shuo],
Automated segmentation and area estimation of neural foramina with boundary regression model,
PR(63), No. 1, 2017, pp. 625-641.
Elsevier DOI 1612
Automated segmentation BibRef

Gu, L.[Lin], Zhang, X.W.[Xiao-Wei], Zhao, H.[He], Li, H.Q.[Hui-Qi], Cheng, L.[Li],
Segment 2D and 3D Filaments by Learning Structured and Contextual Features,
MedImg(36), No. 2, February 2017, pp. 596-606.
IEEE DOI 1702
Retinal vessels, and neurons. BibRef

Li, R.J.[Rong-Jian], Zeng, T.[Tao], Peng, H.C.[Han-Chuan], Ji, S.W.[Shui-Wang],
Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction,
MedImg(36), No. 7, July 2017, pp. 1533-1541.
IEEE DOI 1707
Convolution, Image reconstruction, Image segmentation, Microscopy, Morphology, Neurons, BigNeuron, Deep learning, image denoising, image segmentation, neuron, reconstruction BibRef

Liu, M.[Min], Gong, R.[Rong], Chen, W.[Weixun], Peng, H.C.[Han-Chuan],
3D neuron tip detection in volumetric microscopy images using an adaptive ray-shooting model,
PR(75), No. 1, 2018, pp. 263-271.
Elsevier DOI 1712
Neuron tips BibRef

Krasowski, N.E., Beier, T., Knott, G.W., Köthe, U., Hamprecht, F.A., Kreshuk, A.,
Neuron Segmentation With High-Level Biological Priors,
MedImg(37), No. 4, April 2018, pp. 829-839.
IEEE DOI 1804
Biomembranes, Image edge detection, Image segmentation, Labeling, Neurons, Semantics, Segmentation, automated tracing, connectomics, probabilistic graphical model BibRef

Hilt, P.[Paul], Zarvandi, M.[Maedeh], Kaziakhmedov, E.[Edgar], Bhide, S.[Sourabh], Laptin, M.[Maria], Pape, C.[Constantin], Kreshuk, A.[Anna],
Reinforcement learning for instance segmentation with high-level priors,
BioIm23(3915-3924)
IEEE DOI 2401
BibRef

Liu, S., Zhang, D., Song, Y., Peng, H., Cai, W.,
Automated 3-D Neuron Tracing With Precise Branch Erasing and Confidence Controlled Back Tracking,
MedImg(37), No. 11, November 2018, pp. 2441-2452.
IEEE DOI 1811
Neurons, Image reconstruction, Microscopy, Image segmentation, Transforms, neuron morphology BibRef

Skibbe, H., Reisert, M., Nakae, K., Watakabe, A., Hata, J., Mizukami, H., Okano, H., Yamamori, T., Ishii, S.,
PAT: Probabilistic Axon Tracking for Densely Labeled Neurons in Large 3-D Micrographs,
MedImg(38), No. 1, January 2019, pp. 69-78.
IEEE DOI 1901
Axons, Image reconstruction, Spatial resolution, Microscopy, Monte Carlo methods, image segmentation BibRef

Funke, J.[Jan], Tschopp, F.[Fabian], Grisaitis, W.[William], Sheridan, A.[Arlo], Singh, C.[Chandan], Saalfeld, S.[Stephan], Turaga, S.C.[Srinivas C.],
Large Scale Image Segmentation with Structured Loss Based Deep Learning for Connectome Reconstruction,
PAMI(41), No. 7, July 2019, pp. 1669-1680.
IEEE DOI 1906
neuron segmentation from electron microscopy (EM). Training, Image segmentation, Image reconstruction, Neurons, Microscopy, Prediction algorithms, agglomeration BibRef

Górriz, J.M.[Juan M.], Ramirez, J.[Javier], Suckling, J.[John],
On the computation of distribution-free performance bounds: Application to small sample sizes in neuroimaging,
PR(93), 2019, pp. 1-13.
Elsevier DOI 1906
Resubsitution error estimate, Lineal classifiers, Upper bounds, Neuroimaging, VC dimension BibRef

Tang, R., Ketcha, M., Badea, A., Calabrese, E.D., Margulies, D.S., Vogelstein, J.T., Priebe, C.E., Sussman, D.L.,
Connectome smoothing via low-rank approximations,
MedImg(38), No. 6, June 2019, pp. 1446-1456.
IEEE DOI 1906
Sociology, Matrix decomposition, Imaging, Brain, Maximum likelihood estimation, Networks, connectome, low-rank, estimation BibRef

Yi, J.R.[Jing-Ru], Wu, P.X.[Peng-Xiang], Metaxas, D.N.[Dimitris N.],
ASSD: Attentive single shot multibox detector,
CVIU(189), 2019, pp. 102827.
Elsevier DOI 1911
Object detection, Attention, Single shot detection BibRef

Yi, J.R.[Jing-Ru], Wu, P.X.[Peng-Xiang], Jiang, M.[Menglin], Hoeppner, D.J.[Daniel J.], Metaxas, D.N.[Dimitris N.],
Instance Segmentation of Neural Cells,
BioIm18(VI:395-402).
Springer DOI 1905
BibRef

Li, Q., Shen, L.,
3D Neuron Reconstruction in Tangled Neuronal Image With Deep Networks,
MedImg(39), No. 2, February 2020, pp. 425-435.
IEEE DOI 2002
Neurons, Image reconstruction, Image segmentation, Convolution, Morphology, 3D U-Net Plus BibRef

Zhao, J.[Jie], Chen, X.J.[Xue-Jin], Xiong, Z.W.[Zhi-Wei], Liu, D.[Dong], Zeng, J.J.[Jun-Jie], Xie, C.Y.[Chao-Yu], Zhang, Y.Y.[Yue-Yi], Zha, Z.J.[Zheng-Jun], Bi, G.Q.[Guo-Qiang], Wu, F.[Feng],
Neuronal Population Reconstruction From Ultra-Scale Optical Microscopy Images via Progressive Learning,
MedImg(39), No. 12, December 2020, pp. 4034-4046.
IEEE DOI 2012
Image reconstruction, Sociology, Statistics, Neurites, Noise measurement, Manuals, Neuronal population reconstruction, progressive learning BibRef

Chen, X.J.[Xue-Jin], Zhang, C.[Chi], Zhao, J.[Jie], Xiong, Z.W.[Zhi-Wei], Zha, Z.J.[Zheng-Jun], Wu, F.[Feng],
Weakly Supervised Neuron Reconstruction From Optical Microscopy Images With Morphological Priors,
MedImg(40), No. 11, November 2021, pp. 3205-3216.
IEEE DOI 2111
Neurons, Image reconstruction, Image segmentation, Feature extraction, Morphology, Generative adversarial networks, weakly supervised BibRef

Jiang, Y., Chen, W., Liu, M., Wang, Y., Meijering, E.,
3D Neuron Microscopy Image Segmentation via the Ray-Shooting Model and a DC-BLSTM Network,
MedImg(40), No. 1, January 2021, pp. 26-37.
IEEE DOI 2012
Image segmentation, Neurons, Feature extraction, Microscopy, Solid modeling, Training, neuron reconstruction BibRef

Chen, W., Liu, M., Zhan, Q., Tan, Y., Meijering, E., Radojevic, M., Wang, Y.,
Spherical-Patches Extraction for Deep-Learning-Based Critical Points Detection in 3D Neuron Microscopy Images,
MedImg(40), No. 2, February 2021, pp. 527-538.
IEEE DOI 2102
Neurons, Microscopy, Image reconstruction, microscopy images BibRef

Lee, K.[Kisuk], Lu, R.[Ran], Luther, K.[Kyle], Seung, H.S.[H. Sebastian],
Learning and Segmenting Dense Voxel Embeddings for 3D Neuron Reconstruction,
MedImg(40), No. 12, December 2021, pp. 3801-3811.
IEEE DOI 2112
Neurons, Image segmentation, Measurement, Image reconstruction, Semantics, neuron reconstruction BibRef

Maheswari, P.U.[P. Uma], Banumathi, A., Ulaganathan, G., Yoganandha, R.,
Inferior alveolar nerve canal segmentation by local features based neural network model,
IET-IPR(16), No. 3, 2022, pp. 703-716.
DOI Link 2202
BibRef

Song, P.F.[Ping-Fan], Verinaz-Jadan, H.[Herman], Howe, C.L.[Carmel L.], Foust, A.J.[Amanda J.], Dragotti, P.L.[Pier Luigi],
Light-Field Microscopy for the Optical Imaging of Neuronal Activity: When model-based methods meet data-driven approaches,
SPMag(39), No. 2, March 2022, pp. 58-72.
IEEE DOI 2203
Microscopy, Computational modeling, Neurons, Social factors, Signal processing algorithms, Optical imaging, Machine learning BibRef

Song, P.F.[Ping-Fan], Jadan, H.V.[Herman Verinaz], Howe, C.L.[Carmel L.], Foust, A.J.[Amanda J.], Dragotti, P.L.[Pier Luigi],
Model-Based Explainable Deep Learning for Light-Field Microscopy Imaging,
IP(33), 2024, pp. 3059-3074.
IEEE DOI 2405
Imaging, Microscopy, Lenses, Optical imaging, Neurons, Computational modeling, Light-field microscopy, algorithm unrolling BibRef

Yan, W.Z.[Wei-Zheng], Qu, G.[Gang], Hu, W.X.[Wen-Xing], Abrol, A.[Anees], Cai, B.[Biao], Qiao, C.[Chen], Plis, S.M.[Sergey M.], Wang, Y.P.[Yu-Ping], Sui, J.[Jing], Calhoun, V.D.[Vince D.],
Deep Learning in Neuroimaging: Promises and challenges,
SPMag(39), No. 2, March 2022, pp. 87-98.
IEEE DOI 2203
Neuroimaging, Deep learning, Sensitivity and specificity, Data models, Reliability, Biomedical imaging BibRef

Yang, B.[Bo], Liu, M.[Min], Wang, Y.[Yaonan], Zhang, K.[Kang], Meijering, E.[Erik],
Structure-Guided Segmentation for 3D Neuron Reconstruction,
MedImg(41), No. 4, April 2022, pp. 903-914.
IEEE DOI 2204
Image segmentation, Neurons, Image reconstruction, Decoding, Feature extraction, Transforms, Image segmentation, microscopy images BibRef

Chauvin, L.[Laurent], Kumar, K.[Kuldeep], Desrosiers, C.[Christian], Wells, W.M.[William M.], Toews, M.[Matthew],
Efficient Pairwise Neuroimage Analysis Using the Soft Jaccard Index and 3D Keypoint Sets,
MedImg(41), No. 4, April 2022, pp. 836-845.
IEEE DOI 2204
Magnetic resonance imaging, Kernel, Training, Biomedical imaging, Uncertainty, Task analysis, Neuroimage analysis, family prediction BibRef

Wang, X.[Xuan], Liu, M.[Min], Wang, Y.[Yaonan], Fan, J.W.[Jia-Wang], Meijering, E.[Erik],
A 3D Tubular Flux Model for Centerline Extraction in Neuron Volumetric Images,
MedImg(41), No. 5, May 2022, pp. 1069-1079.
IEEE DOI 2205
Feature extraction, Neurons, Solid modeling, Image reconstruction, Data mining, Skeleton, fluorescence microscopy BibRef

Chen, W.[Weixun], Liu, M.[Min], Du, H.[Hao], Radojevic, M.[Miroslav], Wang, Y.[Yaonan], Meijering, E.[Erik],
Deep-Learning-Based Automated Neuron Reconstruction From 3D Microscopy Images Using Synthetic Training Images,
MedImg(41), No. 5, May 2022, pp. 1031-1042.
IEEE DOI 2205
Neurons, Image reconstruction, Microscopy, Training, Reconstruction algorithms, microscopy images BibRef

Nikoloska, I.[Ivana], Simeone, O.[Osvaldo],
Training Hybrid Classical-Quantum Classifiers via Stochastic Variational Optimization,
SPLetters(29), 2022, pp. 977-981.
IEEE DOI 2205
Neurons, Stochastic processes, Training, Integrated circuit modeling, Optimization, Qubit, Encoding, quantum machine learning BibRef

Couedic, T.L.[Thomas Le], Caillon, R.[Raphael], Rossant, F.[Florence], Joutel, A.[Anne], Urien, H.[Helene], Rajani, R.M.[Rikesh M.],
Deep-learning based segmentation of challenging myelin sheaths,
IPTA20(1-6)
IEEE DOI 2206
Image segmentation, Axons, Spinal cord, Senior citizens, Tools, White matter, Task analysis, deep learning, segmentation, myelin, axon, electron microscopy BibRef

Jia, S.S.[Shan-Shan], Yu, Z.F.[Zhao-Fei], Onken, A.[Arno], Tian, Y.H.[Yong-Hong], Huang, T.J.[Tie-Jun], Liu, J.K.[Jian K.],
Neural System Identification With Spike-Triggered Non-Negative Matrix Factorization,
Cyber(52), No. 6, June 2022, pp. 4772-4783.
IEEE DOI 2207
Retina, Biological system modeling, Biological neural networks, Visualization, Kernel, Integrated circuit modeling, Ganglia, system identification BibRef

Huang, W.[Wei], Chen, C.[Chang], Xiong, Z.W.[Zhi-Wei], Zhang, Y.Y.[Yue-Yi], Chen, X.J.[Xue-Jin], Sun, X.Y.[Xiao-Yan], Wu, F.[Feng],
Semi-Supervised Neuron Segmentation via Reinforced Consistency Learning,
MedImg(41), No. 11, November 2022, pp. 3016-3028.
IEEE DOI 2211
Neurons, Task analysis, Image segmentation, Data models, Perturbation methods, Training, Information filters, electron microscopy images BibRef

Liu, C.[Chao], Wang, D.L.[De-Li], Zhang, H.[Han], Wu, W.[Wei], Sun, W.Z.[Wen-Zhi], Zhao, T.[Ting], Zheng, N.G.[Neng-Gan],
Using Simulated Training Data of Voxel-Level Generative Models to Improve 3D Neuron Reconstruction,
MedImg(41), No. 12, December 2022, pp. 3624-3635.
IEEE DOI 2212
Neurons, Image segmentation, Data models, Image reconstruction, Training data, Training, Microscopy, Neuron reconstruction, image segmentation BibRef

Zhu, T.F.[Tian-Fang], Yao, G.[Gang], Hu, D.[Dongli], Xie, C.C.[Chuang-Chuang], Li, P.C.[Peng-Cheng], Yang, X.Q.[Xiao-Quan], Gong, H.[Hui], Luo, Q.M.[Qing-Ming], Li, A.[Anan],
Data-Driven Morphological Feature Perception of Single Neuron With Graph Neural Network,
MedImg(42), No. 10, October 2023, pp. 3069-3079.
IEEE DOI 2310
BibRef

Xie, G.Y.[Guo-Yang], Huang, Y.W.[Ya-Wen], Wang, J.B.[Jin-Bao], Lyu, J.Y.[Jia-Yi], Zheng, F.[Feng], Zheng, Y.F.[Ye-Feng], Jin, Y.C.[Yao-Chu],
Cross-Modality Neuroimage Synthesis: A Survey,
Surveys(56), No. 3, October 2023, pp. xx-yy.
DOI Link Code:
WWW Link. 2311
multi-modality neuroimaging synthesis, deep learning, Cross-domain, medical image analysis BibRef

Zhou, H.[Hang], Li, Y.X.[Yu-Xin], Wen, W.[Wu], Yang, H.[Hao], Ma, Y.[Yayu], Chen, M.[Min],
Accurately 3D neuron localization using 2D conv-LSTM super-resolution segmentation network,
IET-IPR(18), No. 2, 2024, pp. 535-547.
DOI Link 2402
biomedical optical imaging, brain, medical image processing, optical microscopy, supervised learning BibRef

Wang, Y.J.[Yi-Jun], Lang, R.[Rui], Li, R.[Rui], Zhang, J.S.[Jun-Song],
NRTR: Neuron Reconstruction With Transformer From 3D Optical Microscopy Images,
MedImg(43), No. 2, February 2024, pp. 886-898.
IEEE DOI 2402
Neurons, Image reconstruction, Transformers, Deep learning, Hidden Markov models, Morphology, Neuron reconstruction, transformer BibRef

Liu, M.[Min], Wu, S.H.[Shu-Han], Chen, R.[Runze], Lin, Z.[Zhuangdian], Wang, Y.[Yaonan], Meijering, E.[Erik],
Brain Image Segmentation for Ultrascale Neuron Reconstruction via an Adaptive Dual-Task Learning Network,
MedImg(43), No. 7, July 2024, pp. 2574-2586.
IEEE DOI 2407
Image segmentation, Feature extraction, Neurons, Image reconstruction, Brain, Task analysis, Image segmentation, dual-task learning BibRef

Li, Z.C.[Zhen-Chen], Yang, X.[Xu], Liu, J.Z.[Jia-Zheng], Hong, B.[Bei], Zhang, Y.C.[Yan-Chao], Zhai, H.[Hao], Shen, L.J.[Li-Jun], Chen, X.[Xi], Liu, Z.Y.[Zhi-Yong], Han, H.[Hua],
DeepMulticut: Deep Learning of Multicut Problem for Neuron Segmentation From Electron Microscopy Volume,
PAMI(46), No. 12, December 2024, pp. 8696-8714.
IEEE DOI 2411
Optimization, Deep learning, Neurons, Pipelines, Task analysis, Estimation, Costs, Neuron segmentation, electron microscopy (EM), combinatorial optimization BibRef


Liu, X.Y.[Xiao-Yu], Cai, M.M.[Miao-Miao], Chen, Y.[Yinda], Zhang, Y.[Yueyi], Shi, T.[Te], Zhang, R.[Ruobing], Chen, X.J.[Xue-Jin], Xiong, Z.W.[Zhi-Wei],
Cross-dimension Affinity Distillation for 3D EM Neuron Segmentation,
CVPR24(11104-11113)
IEEE DOI Code:
WWW Link. 2410
Knowledge engineering, Solid modeling, Accuracy, Neuroscience, Neurons, Morphology, EM Neuron Segmentation, Distillation BibRef

Zhu, D.[Daiyi], Chen, Q.H.[Qi-Hua], Chen, X.J.[Xue-Jin],
Self-Supervised Learning of Skeleton-Aware Morphological Representation for 3D Neuron Segments,
3DV24(1436-1445)
IEEE DOI 2408
Cerebral cortex, Shape, Neurons, Surface morphology, Morphology, Feature extraction, Morphological representation, Neuron classification BibRef

Shamsi, N.I.[Nina I.], Xu, A.S.[Alec S.], Gjesteby, L.A.[Lars A.], Brattain, L.J.[Laura J.],
Improved Topological Preservation in 3D Axon Segmentation and Centerline Detection using Geometric Assessment-driven Topological Smoothing (GATS),
WACV24(7990-7999)
IEEE DOI 2404
Measurement, Axons, Image segmentation, Solid modeling, Smoothing methods, Annotations, Applications BibRef

Xu, A.S.[Alec S.], Shamsi, N.I.[Nina I.], Gjesteby, L.A.[Lars A.], Brattain, L.J.[Laura J.],
Self-Supervised Edge Detection Reconstruction for Topology-Informed 3D Axon Segmentation and Centerline Detection,
WACV24(7816-7824)
IEEE DOI 2404
Training, Axons, Solid modeling, Image edge detection, Brain modeling, Data models, Applications, Biomedical / healthcare / medicine BibRef

Dinsdale, N.K.[Nicola K], Jenkinson, M.[Mark], Namburete, A.I.[Ana IL],
SFHarmony: Source Free Domain Adaptation for Distributed Neuroimaging Analysis,
ICCV23(11460-11471)
IEEE DOI Code:
WWW Link. 2401
BibRef

Lumetti, L.[Luca], Pipoli, V.[Vittorio], Bolelli, F.[Federico], Grana, C.[Costantino],
Annotating the Inferior Alveolar Canal: The Ultimate Tool,
CIAP23(I:525-536).
Springer DOI 2312
BibRef

Wang, Y.Q.[Yi-Qun], Skorokhodov, I.[Ivan], Wonka, P.[Peter],
PET-NeuS: Positional Encoding Tri-Planes for Neural Surfaces,
CVPR23(12598-12607)
IEEE DOI 2309
BibRef

O'Mahony, L.[Laura], Andrearczyk, V.[Vincent], Müller, H.[Henning], Graziani, M.[Mara],
Disentangling Neuron Representations with Concept Vectors,
XAI4CV23(3770-3775)
IEEE DOI 2309
BibRef

Czolbe, S.[Steffen], Dalca, A.V.[Adrian V.],
Neuralizer: General Neuroimage Analysis without Re-Training,
CVPR23(6217-6230)
IEEE DOI 2309
BibRef

Liu, X.Y.[Xiao-Yu], Hu, B.[Bo], Li, M.X.[Ming-Xing], Huang, W.[Wei], Zhang, Y.[Yueyi], Xiong, Z.W.[Zhi-Wei],
A Soma Segmentation Benchmark in Full Adult Fly Brain,
CVPR23(7402-7411)
IEEE DOI 2309
BibRef

Zhao, R.[Runkai], Wang, H.[Heng], Zhang, C.Y.[Chao-Yi], Cai, W.D.[Wei-Dong],
PointNeuron: 3D Neuron Reconstruction via Geometry and Topology Learning of Point Clouds,
WACV23(5776-5786)
IEEE DOI 2302
Point cloud compression, Geometry, Image segmentation, Surface reconstruction, Neurons, Skeleton, 3D computer vision BibRef

Xu, B.L.[Bao-Lei], Li, X.J.[Xiao-Jie], Shi, C.H.[Cang-Hong],
Online Neural Fiber Classification Method based on Lightweight Neural Network,
ICIVC22(442-448)
IEEE DOI 2301
Image registration, Uncertainty, Neural networks, Manuals, Optical fiber networks, Robustness, Classification algorithms, Image processing algorithm BibRef

Zhuang, P.X.[Pei-Xian], Wu, J.[Jiamin],
Reinforcing Neuron Extraction from Calcium Imaging Data via Depth-Estimation Constrained Nonnegative Matrix Factorization,
ICIP22(216-220)
IEEE DOI 2211
Atmospheric modeling, Neurons, Estimation, Scattering, Imaging, Channel estimation, Brain modeling, Neuron extraction, nonnegative matrix factorization BibRef

Cipriano, M.[Marco], Allegretti, S.[Stefano], Bolelli, F.[Federico], Pollastri, F.[Federico], Grana, C.[Costantino],
Improving Segmentation of the Inferior Alveolar Nerve through Deep Label Propagation,
CVPR22(21105-21114)
IEEE DOI 2210
Deep learning, Training, Solid modeling, Irrigation, Annotations, Data models, Datasets and evaluation, Deep learning architectures and techniques BibRef

Balwani, A.[Aishwarya], Miano, J.[Joseph], Liu, R.[Ran], Kitchell, L.[Lindsey], Prasad, J.A.[Judy A.], Johnson, E.C.[Erik C.], Gray-Roncal, W.[William], Dyer, E.L.[Eva L.],
Multi-Scale Modeling of Neural Structure in X-Ray Imagery,
ICIP21(141-145)
IEEE DOI 2201
Deep learning, Image segmentation, Image resolution, Limiting, Brain modeling, Mice, Multi-task learning, brain mapping, X-ray microtomography BibRef

Huang, Y.W.[Ya-Wen], Zheng, F.[Feng], Wang, D.Y.[Dan-Yang], Huang, W.[Weilin], Scott, M.R.[Matthew R.], Shao, L.[Ling],
Brain Image Synthesis with Unsupervised Multivariate Canonical CSC l4Net,
CVPR21(5877-5886)
IEEE DOI 2111
Neuroimaging, Manifolds, Pathology, Image segmentation, Neuroscience, Image synthesis, Robustness BibRef

You, Z., Jiang, M., Shi, Z., Shi, C., Du, S., Liang, J., Herard, A.S., Jan, C., Souedet, N., Delzescaux, T.,
Automated Detection Of Highly Aggregated Neurons In Microscopic Images Of Macaque Brain,
ICIP20(315-319)
IEEE DOI 2011
Neurons, Microscopy, Indexes, Biological materials, Economic indicators, Neuron detection, point annotation, microscopic image BibRef

Pan, X., Ren, Y., Sheng, K., Dong, W., Yuan, H., Guo, X., Ma, C., Xu, C.,
Dynamic Refinement Network for Oriented and Densely Packed Object Detection,
CVPR20(11204-11213)
IEEE DOI 2008
Feature extraction, Kernel, Object detection, Shape, Convolution, Neurons, Training BibRef

Talwar, A., Lin, Z., Wei, D., Wu, Y., Zheng, B., Zhao, J., Jang, W., Wang, X., Lichtman, J., Pfister, H.,
A Topological Nomenclature for 3D Shape Analysis in Connectomics,
Microscopy20(4245-4253)
IEEE DOI 2008
Shape, Neurons, Skeleton, Topology, Neuroscience, Morphology BibRef

Klinghoffer, T., Morales, P., Park, Y., Evans, N., Chung, K., Brattain, L.J.,
Self-Supervised Feature Extraction for 3D Axon Segmentation,
Microscopy20(4213-4219)
IEEE DOI 2008
Task analysis, Axons, Training, Image segmentation, Microscopy BibRef

Kim, E., Rego, J., Watkins, Y., Kenyon, G.T.,
Modeling Biological Immunity to Adversarial Examples,
CVPR20(4665-4674)
IEEE DOI 2008
Retina, Visualization, Machine learning, Biological system modeling, Neurons, Ganglia BibRef

Hwang, S.J., Tao, Z., Singh, V., Kim, W.H.,
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples With Applications to Neuroimaging,
ICCV19(10691-10700)
IEEE DOI 2004
brain, data analysis, diseases, image sequences, medical image processing, neural nets, neurophysiology, Diseases BibRef

Cortés, X.[Xavier], Conte, D.[Donatello], Makris, P.[Pascal],
Nerve Contour Tracking for Ultrasound-Guided Regional Anesthesia,
NTIAP19(244-251).
Springer DOI 1909
BibRef

Parag, T.[Toufiq], Berger, D.[Daniel], Kamentsky, L.[Lee], Staffler, B.[Benedikt], Wei, D.L.[Dong-Lai], Helmstaedter, M.[Moritz], Lichtman, J.W.[Jeff W.], Pfister, H.[Hanspeter],
Detecting Synapse Location and Connectivity by Signed Proximity Estimation and Pruning with Deep Nets,
BioIm18(VI:354-364).
Springer DOI 1905
BibRef

Tan, Y.H.[Ying-Hui], Luo, H.Q.[Hui-Qiong], Wang, X.P.[Xue-Ping], Liu, M.[Min],
Convolutional Neural Network Cascade Based Neuron Termination Detection in 3D Image Stacks,
ICIP18(4048-4052)
IEEE DOI 1809
Neurons, Convolution, Training, Image reconstruction, Convolutional neural network cascade BibRef

Liu, M., Liu, K., Wang, C., Luo, H.,
Local Neuron Radius Estimation in Volumetric Microscopy Images,
ICIP18(3848-3852)
IEEE DOI 1809
Neurons, Estimation, Microscopy, Sampling methods, Mathematical model, Multistencils Fast Marching method BibRef

Batabyal, T., Acton, S.T.,
Elastic Path2Path: Automated Morphological Classification of Neurons by Elastic Path Matching,
ICIP18(166-170)
IEEE DOI 1809
Neurons, Measurement, Shape, Morphology, Feature extraction, Hafnium, elastic curves, neuron matching, quantitative image analysis BibRef

Jimenez, C., Diaz, D., Salazar, D., Alvarez, A.M., Orozco, A.A., Henao, O.A.,
Nerve Structure Segmentation from Ultrasound Images Using Random Under-Sampling and an SVM Classifier,
ICIAR18(571-578).
Springer DOI 1807
BibRef

Chai, X.Q.[Xiao-Qi], Qian, D.[Douglas], Ba, Q.L.[Qin-Le], Li, A.R.[Ang-Ran], Zhang, Y.J.J.[Yong-Jie Jessica], Yang, G.[Ge],
Image-based measurement of cargo traffic flow in complex neurite networks,
ICIP17(3290-3294)
IEEE DOI 1803
Biomedical imaging, Indexes, Neuroscience, Q measurement, image-based measurement, kymograph, network flow, traffic flow BibRef

Liang, H., Acton, S.T., Weller, D.S.,
Content-aware neuron image enhancement,
ICIP17(3510-3514)
IEEE DOI 1803
Image enhancement, Image segmentation, Indexes, Neurons, Skeleton, tubular structure BibRef

Shen, W., Wang, B., Jiang, Y., Wang, Y., Yuille, A.L.,
Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection,
ICCV17(2410-2419)
IEEE DOI 1802
brain models, cellular biophysics, convolution, image reconstruction, image segmentation, BibRef

Tang, Z., Zhang, D., Liu, S., Song, Y., Peng, H., Cai, W.,
Automatic 3D Single Neuron Reconstruction with Exhaustive Tracing,
BioIm17(126-133)
IEEE DOI 1802
Biological neural networks, Image reconstruction, Morphology, Neurons, Skeleton, Transforms BibRef

Kim, H.J., Adluru, N., Suri, H., Vemuri, B.C., Johnson, S.C., Singh, V.,
Riemannian Nonlinear Mixed Effects Models: Analyzing Longitudinal Deformations in Neuroimaging,
CVPR17(5777-5786)
IEEE DOI 1711
Brain modeling, Computational modeling, Data models, Diseases, Manifolds, Measurement, Strain BibRef

He, L., Lu, C.T., Ding, H., Wang, S., Shen, L., Yu, P.S., Ragin, A.B.,
Multi-way Multi-level Kernel Modeling for Neuroimaging Classification,
CVPR17(6846-6854)
IEEE DOI 1711
Data mining, Data models, Diseases, Feature extraction, Kernel, Neuroimaging, Tensile, stress BibRef

Kim, W.H.[Won Hwa], Jalal, M.[Mona], Hwang, S.J.[Seong-Jae], Johnson, S.C.[Sterling C.], Singh, V.[Vikas],
Online Graph Completion: Multivariate Signal Recovery in Computer Vision,
CVPR17(5019-5027)
IEEE DOI 1711
E.g. neuroimaging application. Extraterrestrial measurements, Fourier transforms, Laplace equations, Wavelet, transforms BibRef

Ghani, M.U.[Muhammad Usman], Erdil, E.[Ertunç], Kanik, S.D.[Sümeyra Demir], Argunsah, A.Ö.[Ali Özgür], Hobbiss, A.F.[Anna Felicity], Israely, I.[Inbal], Ünay, D.[Devrim], Tasdizen, T.[Tolga], Çetin, M.[Müjdat],
Dendritic Spine Shape Analysis: A Clustering Perspective,
BioImage16(I: 256-273).
Springer DOI 1611
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Mesbah, R., McCane, B., Mills, S.,
Deep convolutional encoder-decoder for myelin and axon segmentation,
ICVNZ16(1-6)
IEEE DOI 1701
Axons BibRef

An, W.[Wookyung], Choe, Y.[Yoonsuck],
Automated Reconstruction of Neurovascular Networks in Knife-Edge Scanning Microscope Rat Brain Nissl Data Set,
ISVC16(I: 439-448).
Springer DOI 1701
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Xu, K., Su, H., Zhu, J., Guan, J.S., Zhang, B.,
Neuron Segmentation Based on CNN with Semi-Supervised Regularization,
Microscopy16(1324-1332)
IEEE DOI 1612
BibRef

Chakraborty, R., Zhen, X., Vogt, N., Bendlin, B.B., Singh, V.,
Dilated Convolutional Neural Networks for Sequential Manifold-Valued Data,
ICCV19(10620-10630)
IEEE DOI 2004
Convolution, Manifolds, Data models, Machine learning, Kernel, Brain modeling, Geometry BibRef

Kim, W.H.[Won Hwa], Hwang, S.J.[Seong Jae], Adluru, N.[Nagesh], Hwang, S.J.[Seong Jae], Adluru, N.[Nagesh], Collins, M.D., Ravi, S.N., Bendlin, B.B., Johnson, S.C.[Sterling C.], Singh, V.[Vikas],
Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks,
CVPR16(2517-2525)
IEEE DOI 1612
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Johnson, S.C.[Sterling C.], Singh, V.[Vikas],
Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging,
ECCV16(VI: 188-205).
Springer DOI 1611
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Bielecki, A.[Andrzej], Gierdziewicz, M.[Maciej], Kalita, P.[Piotr], Szostek, K.[Kamil],
Construction of a 3D Geometric Model of a Presynaptic Bouton for Use in Modeling of Neurotransmitter Flow,
ICCVG16(377-386).
Springer DOI 1611
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Hadjerci, O., Hafiane, A., Vieyres, P., Conte, D., Makris, P., Delbos, A.,
On-line learning dynamic models for nerve detection in ultrasound videos,
ICIP16(131-135)
IEEE DOI 1610
Computational modeling BibRef

Miolane, N.[Nina], Pennec, X.[Xavier],
A Survey of Mathematical Structures for Extending 2D Neurogeometry to 3D Image Processing,
MCV15(155-167).
Springer DOI 1608
Neurogeometry models the neuronal architecture of the visual cortex through Differential Geometry. Models for 3D medical computer vision. BibRef

Kim, W.H., Ravi, S.N., Johnson, S.C., Okonkwo, O.C., Singh, V.,
On Statistical Analysis of Neuroimages with Imperfect Registration,
ICCV15(666-674)
IEEE DOI 1602
Algorithm design and analysis BibRef

Roncal, W.G.[William Gray], Pekala, M.[Michael], Kaynig-Fittkau, V.[Verena], Kleissas, D.M.[Dean M.], Vogelstein, J.T.[Joshua T.], Pfister, H.[Hanspeter], Burns, R.[Randal], Vogelstein, R.J.[R. Jacob], Chevillet, M.A.[Mark A.], Hager, G.D.[Gregory D.],
VESICLE: Volumetric Evaluation of Synaptic Inferfaces using Computer Vision at Large Scale,
BMVC15(xx-yy).
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Duncan, A.[Adam], Klassen, E.[Eric], Descombes, X.[Xavier], Srivastava, A.[Anuj],
Geometric Analysis of Axonal Tree Structures,
DIFF-CV15(xx-yy).
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McGraw, T.[Tim],
Graph-Based Visualization of Neuronal Connectivity Using Matrix Block Partitioning and Edge Bundling,
ISVC15(I: 3-13).
Springer DOI 1601
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Maier, T.[Tobias], Vetter, T.[Thomas],
Implicit Boundary Learning for Connectomics,
CIAP15(I:39-49).
Springer DOI 1511
neurons in 3D electron microscopy BibRef

Hadjerci, O.[Oussama], Hafiane, A.[Adel], Makris, P.[Pascal], Conte, D.[Donatello], Vieyres, P.[Pierre], Delbos, A.[Alain],
Nerve Localization by Machine Learning Framework with New Feature Selection Algorithm,
CIAP15(I:246-256).
Springer DOI 1511
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Rada, L.[Lavdie], Erdil, E.[Ertunc], Ozgur Argunsah, A., Unay, D.[Devrim], Cetin, M.[Mujdat],
Automatic dendritic spine detection using multiscale dot enhancement filters and SIFT features,
ICIP14(26-30)
IEEE DOI 1502
Feature extraction BibRef

Sokoll, S., Beelitz, H., Heine, M., Tonnies, K.,
Towards automatic reconstruction of axonal structures in volumetric microscopy images depicting only active synapses,
IPTA12(426-431)
IEEE DOI 1503
image reconstruction BibRef

Bowler, J.[John], Feris, R.S.[Rogerio S.], Cao, L.L.[Liang-Liang], Wang, J.[Jun], Zhou, M.[Mo],
Automated Axon Segmentation from Highly Noisy Microscopic Videos,
WACV15(915-920)
IEEE DOI 1503
Feature extraction BibRef

O'Harney, A.D.[Andrew D.], Marquand, A.[Andre], Rubia, K.[Katya], Chantiluke, K.[Kaylita], Smith, A.[Anna], Cubillo, A.[Ana], Blain, C.[Camilla], Filippone, M.[Maurizio],
Pseudo-Marginal Bayesian Multiple-Class Multiple-Kernel Learning for Neuroimaging Data,
ICPR14(3185-3190)
IEEE DOI 1412
Approximation methods BibRef

Hadjerci, O.[Oussama], Hafiane, A.[Adel], Makris, P.[Pascal], Conte, D.[Donatello], Vieyres, P.[Pierre], Delbos, A.[Alain],
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ICIP13(1163-1166)
IEEE DOI 1402
Biomedical imaging BibRef

Mukherjee, S.[Suvadip], Acton, S.T.[Scott T.],
Vector field convolution medialness applied to neuron tracing,
ICIP13(665-669)
IEEE DOI 1402
Convolution BibRef

Zhu, J.[Junda], Yuan, L.[Liang],
Neurofilament tracking by detection in fluorescence microscopy images,
ICIP13(3123-3127)
IEEE DOI 1402
Markov Random Field (MRF); fluorescence microscopy; graph cut BibRef

Jayasuriya, S.A.[Surani Anuradha], Liew, A.W.C.[Alan Wee-Chung],
Fractal Analysis for Symmetry Plane Detection in Neuroimages,
IbPRIA13(181-188).
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Pipeline for Tracking Neural Progenitor Cells,
MCVM12(155-164).
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MEG source reconstruction with basis functions source model,
ICPR12(1791-1794).
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Song, S.M.[Soo-Min], Son, J.[Jeany], Kim, M.H.[Myoung-Hee],
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