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Chapter and Conference Paper
Weakly/Semi-supervised Left Ventricle Segmentation in 2D Echocardiography with Uncertain Region-Aware Contrastive Learning
Segmentation of the left ventricle in 2D echocardiography is essential for cardiac function measures, such as ejection fraction. Fully-supervised algorithms have been used in the past to segment the left ventr...
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Chapter and Conference Paper
Polar-Net: A Clinical-Friendly Model for Alzheimer’s Disease Detection in OCTA Images
Optical Coherence Tomography Angiography (OCTA) is a promising tool for detecting Alzheimer’s disease (AD) by imaging the retinal microvasculature. Ophthalmologists commonly use region-based analysis, such as ...
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Chapter and Conference Paper
Automatically Segment the Left Atrium and Scars from LGE-MRIs Using a Boundary-Focused nnU-Net
Atrial fibrillation (AF) is the most common cardiac arrhythmia. Accurate segmentation of the left atrial (LA) and LA scars can provide valuable information to predict treatment outcomes in AF. In this paper, w...
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Chapter and Conference Paper
Shape-Aware Weakly/Semi-Supervised Optic Disc and Cup Segmentation with Regional/Marginal Consistency
Glaucoma is a chronic eye disease that permanently impairs vision. Vertical cup to disc ratio (vCDR) is essential for glaucoma screening. Thus, accurately segmenting the optic disc (OD) and optic cup (OC) from co...
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Chapter and Conference Paper
NerveFormer: A Cross-Sample Aggregation Network for Corneal Nerve Segmentation
The segmentation of corneal nerves in corneal confocal microscopy (CCM) is of great to the quantification of clinical parameters in the diagnosis of eye-related diseases and systematic diseases. Existing work...
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Chapter and Conference Paper
TransBridge: A Lightweight Transformer for Left Ventricle Segmentation in Echocardiography
Echocardiography is an essential diagnostic method to assess cardiac functions. However, manually labelling the left ventricle region on echocardiography images is time-consuming and subject to observer bias. ...