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Chapter and Conference Paper
Boosting Medical Image Segmentation with Partial Class Supervision
Medical image data are often limited due to expensive acquisition and annotation processes. Directly using such limited annotated samples can easily lead to the deep learning models overfitting on the training...
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Chapter and Conference Paper
CircleFormer: Circular Nuclei Detection in Whole Slide Images with Circle Queries and Attention
Both CNN-based and Transformer-based object detection with bounding box representation have been extensively studied in computer vision and medical image analysis, but circular object detection in medical imag...
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Chapter and Conference Paper
Joint Spinal Centerline Extraction and Curvature Estimation with Row-Wise Classification and Curve Graph Network
Spinal curvature estimation plays an important role in adolescent idiopathic scoliosis (AIS) evaluation and treatment. The Cobb angle is a well-established standard for spinal curvature estimation. Recent stud...
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Chapter and Conference Paper
Structure-Aware Rank-1 Tensor Approximation for Curvilinear Structure Tracking Using Learned Hierarchical Features
Tracking of curvilinear structures (CS), such as vessels and catheters, in X-ray images has become increasingly important in recent interventional applications. However, CS is often barely visible in low-dose X-r...
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Article
Discriminative vessel segmentation in retinal images by fusing context-aware hybrid features
Vessel segmentation is an important problem in medical image analysis and is often challenging due to large variations in vessel appearance and profiles, as well as image noises. To address these challenges, w...
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Chapter
Shape Based Conditional Random Fields for Segmenting Intracranial Aneurysms
Studies have found strong correlation between the risk of rupture of intracranial aneurysms and various physical measurements on the aneurysms, such as volume, surface area, neck length, among others. Accuracy...
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Chapter and Conference Paper
Kernel-Based Motion-Blurred Target Tracking
Motion blurs are pervasive in real captured video data, especially for hand-held cameras and smartphone cameras because of their low frame rate and material quality. This paper presents a novel Kernel-based mo...
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Chapter and Conference Paper
An Improved Model of Producing Saliency Map for Visual Attention System
The iLab Neuromorphic Vision Toolkit (iINVT), steadily kept up to date by the group around Laurent Itti, is one of the currently best known attention systems. Their model of bottom up or saliency-based visual ...
