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We present an in-depth investigation of a fully automated Fourier-based analysis to determine the cell size and the width of its distribution in 3D biological tissues. The results are thoroughly tested using generated images, and we offer…

Biological Physics · Physics 2022-04-26 Tess Homan , Sylvain Monnier , Cécile Jebane , Alice Nicolas , Hélène Delanoe-Ayari

We combine confocal imaging, microfluidics and image analysis to record 3D-images of cells in flow. This enables us to recover the full 3D representation of several hundred living cells per minute. Whereas 3D confocal imaging has thus far…

Fluid Dynamics · Physics 2017-09-19 S. Quint , A. F. Christ , A. Guckenberger , S. Himbert , L. Kaestner , S. Gekle , C. Wagner

Biological cell imaging has become one of the most crucial research interests due to its wide-ranging applications in biomedical and microbiology studies. However, three-dimensional (3D) imaging of biological cells remains critically…

In dense biological tissues, cell types performing different roles remain segregated by maintaining sharp interfaces. To better understand the mechanisms for such sharp compartmentalization, we study the effect of an imposed heterotypic…

Soft Condensed Matter · Physics 2021-10-27 Preeti Sahu , J. M. Schwarz , M. Lisa Manning

In many tissues, cell type varies over single-cell length-scales, creating detailed spatial heterogeneities fundamental to physiological function. To gain understanding of this relationship between tissue function and detailed structure,…

We present a novel method for characterizing the microstructure of a material from volumetric datasets such as 3D image data from computed tomography (CT). The method is based on a new statistical model for the distribution of voxel…

Materials Science · Physics 2021-01-06 Elise Otterlei Brenne , Vedrana Andersen Dahl , Peter Stanley Jørgensen

3D cell segmentation methods are often hindered by \emph{oversegmentation}, where a single cell is incorrectly split into multiple fragments. This degrades the final segmentation quality and is notoriously difficult to resolve, as…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Peter Chen , Bryan Chang , Olivia A Creasey , Julie Beth Sneddon , Zev J Gartner , Yining Liu

Data-driven cell tracking and segmentation methods in biomedical imaging require diverse and information-rich training data. In cases where the number of training samples is limited, synthetic computer-generated data sets can be used to…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 David Wiesner , Julian Suk , Sven Dummer , Tereza Nečasová , Vladimír Ulman , David Svoboda , Jelmer M. Wolterink

This study addresses the challenge of classifying cell shapes from noisy contours, such as those obtained through cell instance segmentation of histological images. We assess the performance of various features for shape classification,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-04 Valentina Vadori , Antonella Peruffo , Jean-Marie Graïc , Livio Finos , Enrico Grisan

A model of multicellular systems with several types of cells is developed from the phase field model. The model is presented as a set of partial differential equations of the field variables, each of which expresses the shape of one cell.…

Biological Physics · Physics 2015-05-30 Makiko Nonomura

An important open question in the modeling of biological tissues is how to identify the right scale for coarse-graining, or equivalently, the right number of degrees of freedom. For confluent biological tissues, both vertex and Voronoi…

Tissues and Organs · Quantitative Biology 2023-06-08 Elizabeth Lawson-Keister , Tao Zhang , M. Lisa Manning

Tracking of plant cells in images obtained by microscope is a challenging problem due to biological phenomena such as large number of cells, non-uniform growth of different layers of the tightly packed plant cells and cell division.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Md Shazid Islam , Arindam Dutta , Calvin-Khang Ta , Kevin Rodriguez , Christian Michael , Mark Alber , G. Venugopala Reddy , Amit K. Roy-Chowdhury

Highly multiplexed microscopy enables rich spatial characterization of tissues at single-cell resolution, yet most analyses rely on two-dimensional sections despite inherently three-dimensional tissue organization. Acquiring dense…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Ido Harlev , Tamar Oukhanov , Raz Ben-Uri , Leeat Keren , Shai Bagon

To insight the relationships between the self-organizing structures of cells, such as the cell clusters, and the properties of biotissues is helpful in revealing the function and designing biomaterial. Traditional random foam model neglects…

Soft Condensed Matter · Physics 2017-06-07 Xiaohua Zhou , Erhu Zhang , Minggang Xia , Jianlin Liu , Shengli Zhang

We consider the problem of accurately identifying cell boundaries and labeling individual cells in confocal microscopy images, specifically, 3D image stacks of cells with tagged cell membranes. Precise identification of cell boundaries,…

Computer Vision and Pattern Recognition · Computer Science 2019-09-06 Jiaxiang Jiang , Po-Yu Kao , Samuel A. Belteton , Daniel B. Szymanski , B. S. Manjunath

Aiming at inferring 3D shapes from 2D images, 3D shape reconstruction has drawn huge attention from researchers in computer vision and deep learning communities. However, it is not practical to assume that 2D input images and their…

Computer Vision and Pattern Recognition · Computer Science 2018-11-30 Yi-Lun Liao , Yao-Cheng Yang , Yu-Chiang Frank Wang

Our goal in this paper is to investigate properties of 3D shape that can be determined from a single image. We define 3D shape attributes -- generic properties of the shape that capture curvature, contact and occupied space. Our first…

Computer Vision and Pattern Recognition · Computer Science 2017-12-05 David F. Fouhey , Abhinav Gupta , Andrew Zisserman

With systems for acquiring 3D surface data being evermore commonplace, it has become important to reliably extract specific shapes from the acquired data. In the presence of noise and occlusions, this can be done through the use of…

Computer Vision and Pattern Recognition · Computer Science 2015-03-30 Alan Brunton , Augusto Salazar , Timo Bolkart , Stefanie Wuhrer

Biomembranes adopt varying morphologies that are vital to cellular functions. Many studies use computational modeling to understand how various mechanochemical factors contribute to membrane shape transformations. Compared to…

Computational Engineering, Finance, and Science · Computer Science 2022-02-23 Cuncheng Zhu , Christopher T. Lee , Padmini Rangamani

We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate the shape directly from priors, we adopt to further improve…

Computer Vision and Pattern Recognition · Computer Science 2022-04-22 Chao Wen , Yinda Zhang , Chenjie Cao , Zhuwen Li , Xiangyang Xue , Yanwei Fu
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