Insight into deep learning for glioma IDH medical image analysis: A systematic review.

Journal: Medicine
PMID:

Abstract

BACKGROUND: Deep learning techniques explain the enormous potential of medical image analysis, particularly in digital pathology. Concurrently, molecular markers have gained increasing significance over the past decade in the context of glioma patients, providing novel insights into diagnosis and more personalized treatment options. Deep learning combined with imaging and molecular analysis enables more accurate prognostication of patients, more accurate treatment plan proposals, and accurate biomarker (IDH) prediction for gliomas. This systematic study examines the development of deep learning techniques for IDH prediction using histopathology images, spanning the period from 2019 to 2023.

Authors

  • Qingqing Lv
    Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410008, Hunan, China.
  • Yihao Liu
    Department of Emergency, The First Medical Center to Chinese People's Liberation Army General Hospital, Beijing, China.
  • Yingnan Sun
  • Minghua Wu
    Division of Rheumatology and Clinical Immunogenetics, Department of Internal Medicine UTHealth Houston TX 77030 USA.