医学成像中的虚拟组织病理学方法--系统综述。

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Muhammad Talha Imran, Imran Shafi, Jamil Ahmad, Muhammad Fasih Uddin Butt, Santos Gracia Villar, Eduardo Garcia Villena, Tahir Khurshaid, Imran Ashraf
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引用次数: 0

摘要

虚拟组织病理学是医学影像领域的一项新兴技术,它利用先进的计算方法分析组织图像,以进行更精确的疾病诊断。传统的组织病理学依赖于人工技术和专业知识,往往导致过程耗时,诊断结果多变。虚拟组织病理学采用机器学习、深度学习和图像处理等技术来模拟染色和增强组织分析,提供了一种更一致、更自动化的方法。本综述探讨了这些方法的优势、局限性和临床应用,重点介绍了虚拟组织病理学方法的最新进展。此外,还确定了未来研究的重要领域,以提高临床诊断的准确性和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Virtual histopathology methods in medical imaging - a systematic review.

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.

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来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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