Abstract: In image segmentation and specifically in medical image segmentation, the soft-Dice loss is often chosen instead of the more traditional cross-entropy loss to improve performance with ...
Abstract: Pathological image segmentation is a cornerstone in medical image analysis and is crucial for tumor detection, tissue classification, and pathological diagnosis. Existing methods face ...
Abstract: Semi-supervised learning has proven highly effective in tackling the challenge of limited labeled training data in medical image segmentation. In general, current approaches, which rely on ...
Abstract: Semi-supervised learning has gained considerable popularity in medical image segmentation tasks due to its capability to reduce reliance on expert-examined annotations. Several mean-teacher ...
Abstract: In medical image segmentation, capturing long-range dependencies is critical for precise segmentation. Convolutional Neural Networks(CNNs)excel at local features, while Transformers ...
President Donald Trump has introduced a “Presidential Walk of Fame” along a noticeable walkway outside the West Wing of the White House. “The Presidential Walk of Fame has arrived on the West Wing ...
Abstract: In this paper, we present UISE, a unified image segmentation framework that achieves efficient performance across various segmentation tasks, eliminating the need for multiple specialized ...
Abstract: Medical image segmentation is a critical task in medical image analysis. However, traditional convolutional neural network (CNN) based methods are limited in modeling long-range dependencies ...
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