TY - JOUR
T1 - Cost-effective broad learning-based ultrasound biomicroscopy with 3D reconstruction for ocular anterior segmentation
AU - Ali, Saba Ghazanfar
AU - Chen, Yan
AU - Sheng, Bin
AU - Li, Huating
AU - Wu, Qiang
AU - Yang, Po
AU - Muhammad, Khan
AU - Yang, Geng
N1 - Publisher Copyright:
© 2020, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2021/11
Y1 - 2021/11
N2 - 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° 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° 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.
AB - 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° 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° 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.
KW - 3D reconstruction
KW - Broad learning system
KW - Iridocorneal angle of anterior chamber
KW - Machine learning
KW - Medical data analytics
KW - Ultrasound biomicroscopy
UR - https://www.scopus.com/pages/publications/85089298297
U2 - 10.1007/s11042-020-09303-9
DO - 10.1007/s11042-020-09303-9
M3 - Article
AN - SCOPUS:85089298297
SN - 1380-7501
VL - 80
SP - 35105
EP - 35122
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
IS - 28-29
ER -