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Chapter and Conference Paper
Hepatocellular Carcinoma Segmentation from Digital Subtraction Angiography Videos Using Learnable Temporal Difference
Automatic segmentation of hepatocellular carcinoma (HCC) in Digital Subtraction Angiography (DSA) videos can assist radiologists in efficient diagnosis of HCC and accurate evaluation of tumors in clinical prac...
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Chapter and Conference Paper
Multi-level Relationship Capture Network for Automated Skin Lesion Recognition
Automated skin lesion recognition of dermoscopy images is effective for improving diagnostic performance. Current popular solutions either leverage a single image to learn better feature representations or tak...
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Chapter and Conference Paper
Clinical-Inspired Network for Skin Lesion Recognition
Automated skin lesion recognition methods are useful for improving the diagnostic accuracy in dermoscopy images. However, several challenges delayed the pace of the development of these methods, including limi...
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Chapter and Conference Paper
Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion
Surgical instrument segmentation is a key component in develo** context-aware operating rooms. Existing works on this task heavily rely on the supervision of a large amount of labeled data, which involve lab...
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Chapter and Conference Paper
Multi-class Skin Lesion Segmentation for Cutaneous T-cell Lymphomas on High-Resolution Clinical Images
Automated skin lesion segmentation is essential to assist doctors in diagnosis. Most methods focus on lesion segmentation of dermoscopy images, while a few focus on clinical images. Nearly all the existing met...