MIRIAM: A machine and deep learning single-cell segmentation and quantification pipeline for multi-dimensional tissue images.

Autor: McKinley ET; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA., Shao J; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA., Ellis ST; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Heiser CN; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Program in Chemical & Physical Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA., Roland JT; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Macedonia MC; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA., Vega PN; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA., Shin S; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA., Coffey RJ; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Lau KS; Epithelial Biology Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.; Program in Chemical & Physical Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.; Department of Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Jazyk: angličtina
Zdroj: Cytometry. Part A : the journal of the International Society for Analytical Cytology [Cytometry A] 2022 Jun; Vol. 101 (6), pp. 521-528. Date of Electronic Publication: 2022 Feb 07.
DOI: 10.1002/cyto.a.24541
Abstrakt: Increasingly, highly multiplexed tissue imaging methods are used to profile protein expression at the single-cell level. However, a critical limitation is the lack of robust cell segmentation tools for tissue sections. We present Multiplexed Image Resegmentation of Internal Aberrant Membranes (MIRIAM) that combines (a) a pipeline for cell segmentation and quantification that incorporates machine learning-based pixel classification to define cellular compartments, (b) a novel method for extending incomplete cell membranes, and (c) a deep learning-based cell shape descriptor. Using human colonic adenomas as an example, we show that MIRIAM is superior to widely utilized segmentation methods and provides a pipeline that is broadly applicable to different imaging platforms and tissue types.
(© 2022 The Authors. Cytometry Part A published by Wiley Periodicals LLC on behalf of International Society for Advancement of Cytometry.)
Databáze: MEDLINE
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