Virtual histopathology methods in medical imaging - a systematic review.

Journal: BMC medical imaging
PMID: 39593024

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.

Authors

  • Muhammad Talha Imran
    College of Electrical and Mechanical Engineering, National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
  • Imran Shafi
    College of Electrical and Mechanical Engineering, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
  • Jamil Ahmad
    College of Software and Convergence Technology, Department of Software, Sejong University, Seoul, Republic of Korea.
  • Muhammad Fasih Uddin Butt
    Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad, 44000, Pakistan.
  • Santos Gracia Villar
    Universidad Europea del Atlantico, Santander, 39011, Spain.
  • Eduardo Garcia Villena
    Universidad Europea del Atlantico, Santander, 39011, Spain.
  • Tahir Khurshaid
    Department of Electrical Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea.
  • Imran Ashraf
    Information and Communication Engineering, Yeungnam University, Gyeongsan si, Daegu, South Korea.

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