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The nematode Caenorhabditis elegans (C. elegans) is used as a model organism to better understand developmental biology and neurobiology. C. elegans features an invariant cell lineage, which has been catalogued and observed using…

Computer Vision and Pattern Recognition · Computer Science 2022-08-03 Andrew Lauziere , Ryan Christensen , Hari Shroff

The detection of cell shape changes in 3D time-lapse images of complex tissues is an important task. However, it is a challenging and tedious task to establish a comprehensive dataset to improve the performance of deep learning models. In…

Image and Video Processing · Electrical Eng. & Systems 2019-06-04 Dali Wang , Zheng Lu , Zhirong Bao

The timing of cell divisions in early embryos during the In-Vitro Fertilization (IVF) process is a key predictor of embryo viability. However, observing cell divisions in Time-Lapse Monitoring (TLM) is a time-consuming process and highly…

Computer Vision and Pattern Recognition · Computer Science 2022-10-11 Tien-Phat Nguyen , Trong-Thang Pham , Tri Nguyen , Hieu Le , Dung Nguyen , Hau Lam , Phong Nguyen , Jennifer Fowler , Minh-Triet Tran , Ngan Le

During developmental processes such as embryogenesis, how a group of cells fold into specific structures, is a central question in biology that defines how living organisms form. Establishing tissue-level morphology critically relies on how…

Soft Condensed Matter · Physics 2024-07-23 Haiqian Yang , Anh Q. Nguyen , Dapeng Bi , Markus J. Buehler , Ming Guo

Tracking many cells in time-lapse 3D image sequences is an important challenging task of bioimage informatics. Motivated by a study of brain-wide 4D imaging of neural activity in C. elegans, we present a new method of multi-cell tracking.…

Computer Vision and Pattern Recognition · Computer Science 2018-01-18 Osamu Hirose , Shotaro Kawaguchi , Terumasa Tokunaga , Yu Toyoshima , Takayuki Teramoto , Sayuri Kuge , Takeshi Ishihara , Yuichi Iino , Ryo Yoshida

Transformers have made remarkable progress towards modeling long-range dependencies within the medical image analysis domain. However, current transformer-based models suffer from several disadvantages: (1) existing methods fail to capture…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Chenyu You , Ruihan Zhao , Fenglin Liu , Siyuan Dong , Sandeep Chinchali , Ufuk Topcu , Lawrence Staib , James S. Duncan

The distribution and interactions of cellular organelles play a critical role in mediating cellular physiology and pathology. Large-scale electron microscopy enables visualization of organelle distribution and interactions at the tissue…

Biological Physics · Physics 2026-02-24 Li Xiao , Liqing Liu , Hongjun Wu , Jiayi Zhong , Xixia Li , Yan Zhang , Junjie Hu , Sun Fei , Ge Yang , Tao Xu

Studying cell morphology changes in time is critical to understanding cell migration mechanisms. In this work, we present a deep learning-based workflow to segment cancer cells embedded in 3D collagen matrices and imaged with phase-contrast…

Computer Vision and Pattern Recognition · Computer Science 2021-12-17 Estibaliz Gómez-de-Mariscal , Hasini Jayatilaka , Özgün Çiçek , Thomas Brox , Denis Wirtz , Arrate Muñoz-Barrutia

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by progressive cognitive decline and widespread epigenetic dysregulation in the brain. DNA methylation, as a stable yet dynamic epigenetic modification,…

Genomics · Quantitative Biology 2026-01-05 Gang Qu , Guanghao Li , Zhongming Zhao

Advances in optical neuroimaging techniques now allow neural activity to be recorded with cellular resolution in awake and behaving animals. Brain motion in these recordings pose a unique challenge. The location of individual neurons must…

Neurons and Cognition · Quantitative Biology 2017-05-22 Jeffrey P. Nguyen , Ashley N. Linder , George S. Plummer , Joshua W. Shaevitz , Andrew M. Leifer

Deep phenotyping is an emerging conceptual paradigm and experimental approach that seeks to measure many aspects of phenotypes and link them to understand the underlying biology. Successful deep phenotyping has mostly been applied in…

Quantitative Methods · Quantitative Biology 2019-04-03 Nan Xu , Dhaval S. Patel , Hang Lu

Signal transduction and cell function are governed by the spatiotemporal organization of membrane-associated molecules. Despite significant advances in visualizing molecular distributions by 3D light microscopy, cell biologists still have…

Quantitative Methods · Quantitative Biology 2023-04-14 Felix Y. Zhou , Andrew Weems , Gabriel M. Gihana , Bingying Chen , Bo-Jui Chang , Meghan Driscoll , Gaudenz Danuser

Tracking cells in time-lapse videos is an essential technique for monitoring cell population dynamics at a single-cell level. Current methods for cell tracking are developed on videos with mostly single, constant signals and do not detect…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Florian Bürger , Martim Dias Gomes , Nica Gutu , Adrián E. Granada , Noémie Moreau , Katarzyna Bozek

3D cell tracking in a living organism has a crucial role in live cell image analysis. Cell tracking in C. elegans has two difficulties. First, cell migration in a consecutive frame is large since they move their head during scanning.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Kaito Shiku , Hiromitsu Shirai , Takeshi Ishihara , Ryoma Bise

Investigating the cellular internalization pathways of single molecules or single nano-objects is important to understanding cell-matter interactions and to applications in drug delivery and discovery. Imaging and tracking the motion of…

Biological Physics · Physics 2015-06-04 Guosong Hong , Justin Z. Wu , Joshua T. Robinson , Hailiang Wang , Bo Zhang , Hongjie Dai

How microorganisms respond to and interact with their environment can vary significantly from individual to individual, which can have important microbiological and ecological implications. However, most microscopy techniques can only…

Tracking all nuclei of an embryo in noisy and dense fluorescence microscopy data is a challenging task. We build upon a recent method for nuclei tracking that combines weakly-supervised learning from a small set of nuclei center point…

Computer Vision and Pattern Recognition · Computer Science 2022-08-25 Peter Hirsch , Caroline Malin-Mayor , Anthony Santella , Stephan Preibisch , Dagmar Kainmueller , Jan Funke

Epigenetic Tracking is a mathematical model of biological cells, originally conceived to study embryonic development. Computer simulations proved the capacity of the model to generate complex 3-dimensional cellular structures, and the…

Cell Behavior · Quantitative Biology 2015-07-07 Alessandro Fontana

Transfer learning has gained attention in medical image analysis due to limited annotated 3D medical datasets for training data-driven deep learning models in the real world. Existing 3D-based methods have transferred the pre-trained models…

Computer Vision and Pattern Recognition · Computer Science 2021-04-29 Eunji Jun , Seungwoo Jeong , Da-Woon Heo , Heung-Il Suk

Biomembranes play a central role in various phenomena like locomotion of cells, cell-cell interactions, packaging of nutrients, and in maintaining organelle morphology and functionality. During these processes, the membranes undergo…

Quantitative Methods · Quantitative Biology 2021-12-01 Debabrata Auddya , Xiaoxuan Zhang , Rahul Gulati , Ritvik Vasan , Krishna Garikipati , Padmini Rangamani , Shiva Rudraraju
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