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Found 6 papers, 2 papers with code
Super-Resolution Based Patch-Free 3D Image Segmentation with High-Frequency Guidance
The framework contains two sub-tasks, of which semantic segmentation is the main task and super resolution is an auxiliary task aiding in rebuilding the high frequency information from the LR input.
Mixed Transformer U-Net For Medical Image Segmentation
Therefore, Vision Transformers have emerged as alternative segmentation structures recently, for their innate ability of capturing long-range correlations through Self-Attention (SA).
Genotype-Guided Radiomics Signatures for Recurrence Prediction of Non-Small-Cell Lung Cancer
The experiments demonstrated that the prediction accuracy can be improved significantly from 78. 61% (existing radiomics method) and 79. 14% (deep learning method) to 83. 28% by the proposed GGR.
Graph-based Pyramid Global Context Reasoning with a Saliency-aware Projection for COVID-19 Lung Infections Segmentation
Our Graph- PGCR module is plug-and-play, which can be integrated into any architecture to improve its performance.
PA-ResSeg: A Phase Attention Residual Network for Liver Tumor Segmentation from Multi-phase CT Images
In this paper, we propose a phase attention residual network (PA-ResSeg) to model multi-phase features for accurate liver tumor segmentation, in which a phase attention (PA) is newly proposed to additionally exploit the images of arterial (ART) phase to facilitate the segmentation of portal venous (PV) phase.
MCGKT-Net: Multi-level Context Gating Knowledge Transfer Network for Single Image Deraining
Rain streak removal in a single image is a very challenging task due to its ill-posed nature in essence.
