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Active mesh and neural network pipeline for cell aggregate segmentation

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Title: Active mesh and neural network pipeline for cell aggregate segmentation
Authors: Smith, M
Sparks, H
Almagro, J
Chaigne, A
Behrens, A
Dunsby, C
Salbreux, G
Item Type: Journal Article
Abstract: Segmenting cells within cellular aggregates in 3D is a growing challenge in cell biology due to improvements in capacity and accuracy of microscopy techniques. Here, we describe a pipeline to segment images of cell aggregates in 3D. The pipeline combines neural network segmentations with active meshes. We apply our segmentation method to cultured mouse mammary gland organoids imaged over 24 h with oblique plane microscopy, a high-throughput light-sheet fluorescence microscopy technique. We show that our method can also be applied to images of mouse embryonic stem cells imaged with a spinning disc microscope. We segment individual cells based on nuclei and cell membrane fluorescent markers, and track cells over time. We describe metrics to quantify the quality of the automated segmentation. Our segmentation pipeline involves a Fiji plugin that implements active mesh deformation and allows a user to create training data, automatically obtain segmentation meshes from original image data or neural network prediction, and manually curate segmentation data to identify and correct mistakes. Our active meshes-based approach facilitates segmentation postprocessing, correction, and integration with neural network prediction.
Issue Date: 2-May-2023
Date of Acceptance: 24-Mar-2023
URI: http://hdl.handle.net/10044/1/103554
DOI: 10.1016/j.bpj.2023.03.038
ISSN: 0006-3495
Publisher: Biophysical Society
Start Page: 1586
End Page: 1599
Journal / Book Title: Biophysical Journal
Volume: 122
Issue: 9
Copyright Statement: © 2023 Biophysical Society. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Publication Status: Published
Online Publication Date: 2023-03-30
Appears in Collections:Physics
Department of Surgery and Cancer
Faculty of Medicine
Faculty of Natural Sciences

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