5 papers
Modality-Invariant Coarse-to-Fine Retinal Image Registration
Bo Wen, Nehal Nailesh Mehta, Melanie Tran +3
Retinal image registration is essential for ophthalmic diagnosis, longitudinal disease monitoring, and multimodal retinal image analysis. Existing retinal registration methods are…
Topology-Preserving Image Segmentation with Spatial-Aware Persistent Feature Matching
Bo Wen, Haochen Zhang, Dirk-Uwe G. Bartsch +3
Topological correctness is critical for segmentation of tubular structures, which pervade in biomedical images. Existing topological segmentation loss functions are primarily based…
Universal Vessel Segmentation for Multi-Modality Retinal Images
Bo Wen, Anna Heinke, Akshay Agnihotri +4
We identify two major limitations in the existing studies on retinal vessel segmentation: (1) Most existing works are restricted to one modality, i.e., the Color Fundus (CF). Howev…
Universal Wavelet Units in 3D Retinal Layer Segmentation
An D. Le, Hung Nguyen, Melanie Tran +6
This paper presents the first study to apply tunable wavelet units (UwUs) for 3D retinal layer segmentation from Optical Coherence Tomography (OCT) volumes. To overcome the limitat…
Tunable Wavelet Unit based Convolutional Neural Network in Optical Coherence Tomography Analysis Enhancement for Classifying Type of Epiretinal Membrane Surgery
An Le, Nehal Mehta, William Freeman +9
In this study, we developed deep learning-based method to classify the type of surgery performed for epiretinal membrane (ERM) removal, either internal limiting membrane (ILM) remo…