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Found 2 papers, 2 papers with code
Combining Self-Training and Hybrid Architecture for Semi-supervised Abdominal Organ Segmentation
Abdominal organ segmentation has many important clinical applications, such as organ quantification, surgical planning, and disease diagnosis.
PHTrans: Parallelly Aggregating Global and Local Representations for Medical Image Segmentation
In this paper, we propose a novel hybrid architecture for medical image segmentation called PHTrans, which parallelly hybridizes Transformer and CNN in main building blocks to produce hierarchical representations from global and local features and adaptively aggregate them, aiming to fully exploit their strengths to obtain better segmentation performance.
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