Title
Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical Tissue.
Abstract
Objective: Ultrahigh-resolution optical coherence microscopy (OCM) has recently demonstrated its potential for accurate diagnosis of human cervical diseases. One major challenge for clinical adoption, however, is the steep learning curve clinicians need to overcome to interpret OCM images. Developing an intelligent technique for computer-aided diagnosis (CADx) to accurately interpret OCM images wi...
Year
DOI
Venue
2018
10.1109/TBME.2018.2890167
IEEE Transactions on Biomedical Engineering
Keywords
Field
DocType
Feature extraction,Biomedical imaging,Lesions,Cervical cancer
Cervical cancer,Computer vision,Pattern recognition,Binary classification,Feature (computer vision),Computer science,Convolutional neural network,Medical imaging,Optical coherence microscopy,Computer-aided diagnosis,Feature extraction,Artificial intelligence
Journal
Volume
Issue
ISSN
66
9
0018-9294
Citations 
PageRank 
References 
0
0.34
0
Authors
13
Name
Order
Citations
PageRank
Yu-Tao Ma131428.89
Tao Xu281.47
Xiaolei Huang3108463.94
Xiaofang Wang4367.83
Canyu Li500.34
Jason Jerwick600.34
Yuan Ning700.34
Xianxu Zeng881.13
Baojin Wang900.34
Yihong Wang1000.34
Zhan Zhang1100.34
Xiaoan Zhang1200.34
Chao Zhou1371.82