CT Liver Segmentation via PVT-based Encoding and Refined Decoding

arXiv:2401.09630v2 Announce Type: replace-cross
Abstract: Accurate liver segmentation from CT scans is essential for effective diagnosis and treatment planning. Computer-aided diagnosis systems promise to improve the precision of liver disease diagnosis, disease progression, and treatment planning. In response to the need, we propose a novel deep learning approach, \textit{\textbf{PVTFormer}}, that is built upon a pretrained pyramid vision transformer (PVT v2) combined with advanced residual upsampling and decoder block. By integrating a refined feature channel approach with a hierarchical decoding strategy, …

arxiv cs.cv decoding eess.iv encoding segmentation type via