Virtual histopathology methods in medical imaging - a systematic review

Imran, Muhammad Talha and Shafi, Imran and Ahmad, Jamil and Butt, Muhammad Fasih Uddin and Gracia Villar, Santos and García Villena, Eduardo and Khurshaid, Tahir and Ashraf, Imran UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, eduardo.garcia@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Virtual histopathology methods in medical imaging - a systematic review. BMC Medical Imaging, 24 (1). ISSN 1471-2342

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Abstract

Virtual histopathology is an emerging technology in medical imaging that utilizes advanced computational methods to analyze tissue images for more precise disease diagnosis. Traditionally, histopathology relies on manual techniques and expertise, often resulting in time-consuming processes and variability in diagnoses. Virtual histopathology offers a more consistent, and automated approach, employing techniques like machine learning, deep learning, and image processing to simulate staining and enhance tissue analysis. This review explores the strengths, limitations, and clinical applications of these methods, highlighting recent advancements in virtual histopathological approaches. In addition, important areas are identified for future research to improve diagnostic accuracy and efficiency in clinical settings.

Item Type:	Article
Uncontrolled Keywords:	Dual contrastive learning, Image-to-image translation, Virtual histopathology, Medical image processing, Computational pathology
Subjects:	Subjects > Biomedicine Subjects > Engineering
Divisions:	Europe University of Atlantic > Research > Scientific Production Ibero-american International University > Research > Scientific Production Ibero-american International University > Research > Scientific Production Universidad Internacional do Cuanza > Research > Scientific Production University of La Romana > Research > Scientific Production
Depositing User:	Sr Bibliotecario
Date Deposited:	12 Dec 2024 08:37
Last Modified:	12 Dec 2024 08:37
URI:	http://repositorio.funiber.org/id/eprint/15623

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