TY  - JOUR
IS  - 1
A1  - Imran, Muhammad Talha
A1  - Shafi, Imran
A1  - Ahmad, Jamil
A1  - Butt, Muhammad Fasih Uddin
A1  - Gracia Villar, Santos
A1  - García Villena, Eduardo
A1  - Khurshaid, Tahir
A1  - Ashraf, Imran
AV  - public
TI  - Virtual histopathology methods in medical imaging - a systematic review
UR  - http://doi.org/10.1186/s12880-024-01498-9
JF  - BMC Medical Imaging
VL  - 24
ID  - uniromana15623
N2  - 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.
SN  - 1471-2342
Y1  - 2024/11//
KW  - Dual contrastive learning
KW  -  Image-to-image translation
KW  -  Virtual histopathology
KW  -  Medical image processing
KW  - 
Computational pathology
ER  -