A review of the application of deep learning in medical image classification and segmentation

By Lei Cai, Jingyang Gao, Di Zhao. Annals of Translational Medicine, 2020

533 citations recorded by the source corpus.

Big medical data mainly include electronic health record data, medical image data, gene information data, etc. Among them, medical image data account for the vast majority of medical data at this stage. How to apply big medical data to clinical practice? This is an issue of great concern to medical and computer researchers, and intelligent imaging and deep learning provide a good answer. This review introduces the application of intelligent imaging and deep learning in the field of big data analysis and early diagnosis of diseases, combining the latest research progress of big data analysis of medical images and the work of our team in the field of big data analysis of medical imagec, especially the classification and segmentation of medical images.

Subfields: Artificial Intelligence, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/3f217e5faf34498df5f90ceb081652c2d934cb0b

Citations in the corpus

• Artificial Convolutional Neural Network in Object Detection and Semantic Segmentation for Medical Imaging Analysis (2021, unknown): “They believed that semantic segmentation algorithm was suitable for analyzing pathological images (38).”