Article Dans Une Revue Computer Methods and Programs in Biomedicine Année : 2023

Multi-Agent Medical Image Segmentation: A Survey

Résumé

During the last decades, the healthcare area has increasingly relied on medical imaging for the diagnosis of a growing number of pathologies. The different types of medical images are mostly manually processed by human radiologists for diseases detection and monitoring. However, such a procedure is time-consuming and relies on expert judgment. The latter can be influenced by a variety of factors. One of the most complicated image processing tasks is image segmentation. Medical image segmentation consists of dividing the input image into a set of regions of interest, corresponding to body tissues and organs. Recently, artificial intelligence (AI) techniques brought researchers attention with their promising results for the image segmentation automation. Among AI-based techniques are those that use the Multi-Agent System (MAS) paradigm. This paper presents a comparative study of the multi-agent approaches dedicated to the segmentation of medical images, recently published in the literature.

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hal-04008558 , version 1 (31-03-2025)

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Mohamed Bennai, Zahia Guessoum, Smaine Mazouzi, Stéphane Cormier, Mohamed Mezghiche. Multi-Agent Medical Image Segmentation: A Survey. Computer Methods and Programs in Biomedicine, 2023, 232, pp.107444. ⟨10.1016/j.cmpb.2023.107444⟩. ⟨hal-04008558⟩

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