Paper Info
Title
Cost-effective broad learning-based ultrasound biomicroscopy with 3D reconstruction for ocular anterior segmentation
Abstract
Anterior Chamber Angle (ACA) assessment plays an important role for the diagnosis of glaucoma. Most of the existing techniques relied on Anterior Segment Optical Coherence Tomography (AS-OCT) or Swept Source Optical Coherence Tomography (SS-OCT). We proposed a system for 360 degrees overview of iridocorneal angle of anterior chamber (ICAAC) via Ultrasound Biomicroscopy (UBM). UBM approach acquires the visualization of anterior segment components as well as diseased structures (glaucoma). Our system consists of a new pairing scheme of feature descriptors, i.e. (FREAK, BRISK), (SURF, BRISK) and Broad Learning System (BLS) for 3D reconstruction and segmentation of ICAAC. The 360 degrees overview of 2D ICAAC gives global conception for ACA assessment. 3D images provide a detailed assessment with the amount of opposition's and synechiae in angle-closure suspects, angle-closure and angle-closure glaucoma in bright light conditions. Extensive evaluations are performed on dataset consists of 650 ICAAC images in five directions of 65 subjects with 10 samples per subject (5 left eye and 5 right eye) from Shanghai Sixth People's Hospital. Experiments showed that our approach achieves an overall accuracy of 98.72% with training and testing time 29.26(s), 1.232(s) respectively.
Year
DOI
Venue
2021
10.1007/s11042-020-09303-9
MULTIMEDIA TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Medical data analytics, Machine learning, Broad learning system, 3D reconstruction, Ultrasound biomicroscopy, Iridocorneal angle of anterior chamber
Journal
80
Issue
ISSN
Citations 
28-29
1380-7501
1
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Saba Ghazanfar Ali111.35
Yan Chen2141.22
Bin Sheng3258.13
Huating Li4225.14
Qiang Wu5132.91
Po Yang66412.75
Khan Muhammad798667.67
Geng Yang810.34