7 Result(s)
within
Health Informatics
Yalin Zheng
Chapter
-
Chapter and Conference Paper
Cross-Domain Depth Estimation Network for 3D Vessel Reconstruction in OCT Angiography
Optical Coherence Tomography Angiography (OCTA) has been widely used by ophthalmologists for decision-making due to its superiority in providing caplillary details. Many of the OCTA imaging devices used in cli...
-
Chapter and Conference Paper
Learning Unsupervised Parameter-Specific Affine Transformation for Medical Images Registration
Affine registration has recently been formulated using deep learning frameworks to establish spatial correspondences between different images. In this work, we propose a new unsupervised model that investigate...
-
Chapter and Conference Paper
CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation
The detection of curvilinear structures in medical images, e.g., blood vessels or nerve fibers, is important in aiding management of many diseases. In this work, we propose a general unifying curvilinear struc...
-
Chapter and Conference Paper
Exploiting Reliability-Guided Aggregation for the Assessment of Curvilinear Structure Tortuosity
The study on tortuosity of curvilinear structures in medical images has been significant in support of the examination and diagnosis for a number of diseases. To avoid the bias that may arise from using one p...
-
Chapter and Conference Paper
Uniqueness-Driven Saliency Analysis for Automated Lesion Detection with Applications to Retinal Diseases
Saliency is important in medical image analysis in terms of detection and segmentation tasks. We propose a new method to extract uniqueness-driven saliency based on the uniqueness of intensity and spatial dist...
-
Chapter and Conference Paper
Retinal Artery and Vein Classification via Dominant Sets Clustering-Based Vascular Topology Estimation
The classification of the retinal vascular tree into arteries and veins is important in understanding the relation between vascular changes and a wide spectrum of diseases. In this paper, we have proposed a no...
-
Chapter and Conference Paper
Fast Blur Detection and Parametric Deconvolution of Retinal Fundus Images
Blur is a significant problem in medical imaging which can hinder diagnosis and prevent further automated or manual processing. The problem of restoring an image from blur degradation remains a challenging tas...
