relation: http://repositorio.unib.org/id/eprint/15623/
canonical: http://repositorio.unib.org/id/eprint/15623/
title: Virtual histopathology methods in medical imaging - a systematic review
creator: Imran, Muhammad Talha
creator: Shafi, Imran
creator: Ahmad, Jamil
creator: Butt, Muhammad Fasih Uddin
creator: Gracia Villar, Santos
creator: García Villena, Eduardo
creator: Khurshaid, Tahir
creator: Ashraf, Imran
subject: Biomedicine
subject: Engineering
description: 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.
date: 2024-11
type: Article
type: PeerReviewed
format: text
language: en
rights: cc_by_nc_nd_4
identifier: http://repositorio.unib.org/id/eprint/15623/1/s12880-024-01498-9.pdf
identifier:   Article Subjects > Biomedicine <http://repositorio.unib.org/view/subjects/uneat=5Fbm.html> Subjects > Engineering <http://repositorio.unib.org/view/subjects/uneat=5Feng.html> Europe University of Atlantic > Research > Scientific Production <http://repositorio.unib.org/view/divisions/uneatlantico=5Fproduccion=5Fcientifica.html> Ibero-american International University > Research > Scientific Production <http://repositorio.unib.org/view/divisions/uninimx=5Fproduccion=5Fcientifica.html> Ibero-american International University > Research > Articles and Books <http://repositorio.unib.org/view/divisions/uninipr=5Fproduccion=5Fcientifica.html> Universidad Internacional do Cuanza > Research > Scientific Production <http://repositorio.unib.org/view/divisions/unic=5Fproduccion=5Fcientifica.html> University of La Romana > Research > Scientific Production <http://repositorio.unib.org/view/divisions/uniromana=5Fproduccion=5Fcientifica.html> Open English 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. metadata Imran, Muhammad Talha; Shafi, Imran; Ahmad, Jamil; Butt, Muhammad Fasih Uddin; Gracia Villar, Santos; García Villena, Eduardo; Khurshaid, Tahir and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, eduardo.garcia@uneatlantico.es, UNSPECIFIED, UNSPECIFIED     <http://repositorio.unib.org/id/eprint/15623/1/s12880-024-01498-9.pdf>     (2024) Virtual histopathology methods in medical imaging - a systematic review.  BMC Medical Imaging, 24 (1).   ISSN 1471-2342     
relation: http://doi.org/10.1186/s12880-024-01498-9
relation: doi:10.1186/s12880-024-01498-9
language: en