2026-04-23T05:02:36Zhttps://repisalud.isciii.es/rest/oai/request
oai:repisalud.isciii.es:20.500.12105/157312024-09-27T08:01:38Zcom_20.500.12105_19604com_20.500.12105_2051col_20.500.12105_19605
Repisalud author Molina-Moreno, Miguel author González-Díaz, Iván author Sicilia, Jon author Crainiciuc, Georgiana author Palomino-Segura, Miguel author Hidalgo, Andres author Díaz-de-María, Fernando funder Ministerio de Economía y Competitividad (España) funder Comunidad de Madrid (España) funder Carlos III University of Madrid (España) funder Ministerio de Ciencia e Innovación (España) funder Fundación La Caixa funder Ministerio de Educación, Cultura y Deporte (España) 2023-04-03T11:24:19Z 2023-04-03T11:24:19Z 2022-04 Med Image Anal. 2022 Apr;77:102358 http://hdl.handle.net/20.500.12105/15731 35066392 10.1016/j.media.2022.102358 1361-8423 Medical image analysis Cell detection and tracking applied to in vivo fluorescence microscopy has become an essential tool in biomedicine to characterize 4D (3D space plus time) biological processes at the cellular level. Traditional approaches to cell motion analysis by microscopy imaging, although based on automatic frameworks, still require manual supervision at some points of the system. Hence, when dealing with a large amount of data, the analysis becomes incredibly time-consuming and typically yields poor biological information. In this paper, we propose a fully-automated system for segmentation, tracking and feature extraction of migrating cells within blood vessels in 4D microscopy imaging. Our system consists of a robust 3D convolutional neural network (CNN) for joint blood vessel and cell segmentation, a 3D tracking module with collision handling, and a novel method for feature extraction, which takes into account the particular geometry in the cell-vessel arrangement. Experiments on a large 4D intravital microscopy dataset show that the proposed system achieves a significantly better performance than the state-of-the-art tools for cell segmentation and tracking. Furthermore, we have designed an analytical method of cell behaviors based on the automatically extracted features, which supports the hypotheses related to leukocyte migration posed by expert biologists. This is the first time that such a comprehensive automatic analysis of immune cell migration has been performed, where the total population under study reaches hundreds of neutrophils and thousands of time instances. eng ACME: Automatic feature extraction for cell migration examination through intravital microscopy imaging. journal article 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 URL https://repisalud.isciii.es/bitstreams/40364b1c-8d17-451e-b27d-b75768cefa8c/download File MD5 d250bb16ac95100da02bb744aaa5674c 5641599 application/pdf ACME_ Automatic feature Med Image Anal 2022.pdf URL https://repisalud.isciii.es/bitstreams/025c046c-9ad0-4f08-92c2-e05355032150/download File MD5 5c865003cdbafc7ba0022ae382def61d 103378 text/plain ACME_ Automatic feature Med Image Anal 2022.pdf.txt