Artificial Convolutional Neural Network in Object Detection and Semantic Segmentation for Medical Imaging Analysis
Year: 2021
Type: review
Abstract: In the era of digital medicine, a vast number of medical images are produced every day. There is a great demand for intelligent equipment for adjuvant diagnosis to assist medical doctors with different disciplines. With the development of artificial intelligence, the algorithms of convolutional neural network (CNN) progressed rapidly. CNN and its extension algorithms play important roles on medical imaging classification, object detection, and semantic segmentation. While medical imaging classification has been widely reported, the object detection and semantic segmentation of imaging are rarely described. In this review article, we introduce the progression of object detection and semantic segmentation in medical imaging study. We also discuss how to accurately define the location and boundary of diseases.
Source: Frontiers in Oncology
Authors: Ruixin Yang, Yingyan Yu
Institutions: Shanghai Jiao Tong University, Ruijin Hospital
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,950
OpenAlex ID: W3133661165