scholarly journals Shared-hole graph search with adaptive constraints for 3D optic nerve head optical coherence tomography image segmentation

2018 ◽  
Vol 9 (3) ◽  
pp. 962 ◽  
Author(s):  
Kai Yu ◽  
Fei Shi ◽  
Enting Gao ◽  
Weifang Zhu ◽  
Haoyu Chen ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Image Segmentation ◽  
Optic Nerve ◽  
Optic Nerve Head ◽  
Graph Search ◽  
Optical Coherence Tomography Image ◽  
Optical Coherence ◽  
Tomography Image ◽  
Adaptive Constraints

scholarly journals Unraveling the deep learning gearbox in optical coherence tomography image segmentation towards explainable artificial intelligence

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Peter M. Maloca ◽  
Philipp L. Müller ◽  
Aaron Y. Lee ◽  
Adnan Tufail ◽  
Konstantinos Balaskas ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Optical Coherence Tomography ◽  
Image Segmentation ◽  
Convolutional Neural Network ◽  
Learning Algorithm ◽  
Ground Truth ◽  
Optical Coherence Tomography Image ◽  
Optical Coherence ◽  
Tomography Image

AbstractMachine learning has greatly facilitated the analysis of medical data, while the internal operations usually remain intransparent. To better comprehend these opaque procedures, a convolutional neural network for optical coherence tomography image segmentation was enhanced with a Traceable Relevance Explainability (T-REX) technique. The proposed application was based on three components: ground truth generation by multiple graders, calculation of Hamming distances among graders and the machine learning algorithm, as well as a smart data visualization (‘neural recording’). An overall average variability of 1.75% between the human graders and the algorithm was found, slightly minor to 2.02% among human graders. The ambiguity in ground truth had noteworthy impact on machine learning results, which could be visualized. The convolutional neural network balanced between graders and allowed for modifiable predictions dependent on the compartment. Using the proposed T-REX setup, machine learning processes could be rendered more transparent and understandable, possibly leading to optimized applications.

scholarly journals A Morphological Study of Retinal Changes in Unilateral Amblyopia Using Optical Coherence Tomography Image Segmentation

PLoS ONE ◽  
2014 ◽  
Vol 9 (2) ◽  
pp. e88363 ◽  
Author(s):  
Andrea Szigeti ◽  
Erika Tátrai ◽  
Anna Szamosi ◽  
Péter Vargha ◽  
Zoltán Zsolt Nagy ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Image Segmentation ◽  
Morphological Study ◽  
Optical Coherence Tomography Image ◽  
Optical Coherence ◽  
Tomography Image

scholarly journals Thickness Profiles of Retinal Layers by Optical Coherence Tomography Image Segmentation

2008 ◽  
Vol 146 (5) ◽  
pp. 679-687.e1 ◽  
Author(s):  
Ahmet Murat Bagci ◽  
Mahnaz Shahidi ◽  
Rashid Ansari ◽  
Michael Blair ◽  
Norman Paul Blair ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Image Segmentation ◽  
Optical Coherence Tomography Image ◽  
Optical Coherence ◽  
Retinal Layers ◽  
Tomography Image
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