Editorial: Computational Pathology

Frontiers in Medicine

article

Behzad Bozorgtabar¹  Dwarikanath Mahapatra³  Inti Zlobec⁴  Tilman T. Rau⁴  Jean-Philippe Thiran¹ 

[1] École Polytechnique Fédérale de Lausanne (EPFL);Department of Radiology, University Hospital Center (CHUV);Inception Institute of Artificial Intelligence, United Arab Emirates;Faculty of Medicine, Institute of Pathology, University of Bern

关键词: histopathology images;    image analysis techniques;    deep learning;    clinical outcome analysis;    computer-aided diagnosis;   

DOI  :  10.3389/fmed.2020.00245

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

The huge amount of information and data available in histopathology images, and ease of their digitization has rapidly advanced the field of computational pathology. The effectiveness of computational pathology, coupled with impressive recent advances in the fields of deep learning and computer vision, provide an ideal setting to revolutionize established clinical workflows. The goal of this Research Topic is to publish the latest research advances and bring together scientific researchers, medical experts, and industry partners working in the field of computational pathology for clinical outcome analysis. Emerging technologies such as whole slide imaging (WSI), have increasingly been used to improve the assessment of histological features with several advantages such as easy image accessibility and storage, portability, sharing, annotation, qualitative and quantitative image analysis, and use for diagnostic purposes, including routine diagnosis of liver specimens. The first highlight of this Research Topic is an article entitled “Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders,” by Melo et al. This article presents the review of current knowledge on the application of WSI to histopathological analyses of liver disorders as well as to understand liver biology. This article also addresses how WSI may improve the assessment and quantification of multiple histological parameters in the liver, and help diagnose several hepatic conditions with important clinical implications.

【 授权许可】

CC BY