research
∙
09/07/2023
A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ Segmentation
Although deep learning have revolutionized abdominal multi-organ segment...
share
research
∙
08/30/2023
SAM-Med2D
The Segment Anything Model (SAM) represents a state-of-the-art research ...
research
∙
07/26/2023
Artifact Restoration in Histology Images with Diffusion Probabilistic Models
Histological whole slide images (WSIs) can be usually compromised by art...
research
∙
04/13/2023
STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training
Large-scale models pre-trained on large-scale datasets have profoundly a...
research
∙
03/10/2023
Generative Model Based Noise Robust Training for Unsupervised Domain Adaptation
Target domain pseudo-labelling has shown effectiveness in unsupervised d...
research
∙
03/08/2023
FCN+: Global Receptive Convolution Makes FCN Great Again
Fully convolutional network (FCN) is a seminal work for semantic segment...
research
∙
10/14/2022
Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT Scans
Tumor lesion segmentation is one of the most important tasks in medical ...
research
∙
09/06/2022
An evaluation of U-Net in Renal Structure Segmentation
Renal structure segmentation from computed tomography angiography (CTA) ...
research
∙
05/17/2022
Vision Transformer Adapter for Dense Predictions
This work investigates a simple yet powerful adapter for Vision Transfor...
research
∙
03/23/2022
StructToken : Rethinking Semantic Segmentation with Structural Prior
In this paper, we present structure token (StructToken), a new paradigm ...
research
∙
03/09/2022
Dynamic Instance Domain Adaptation
Most existing studies on unsupervised domain adaptation (UDA) assume tha...
research
∙
09/26/2021
A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images
Radiation therapy (RT) is widely employed in the clinic for the treatmen...
research
∙
09/26/2021
Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation
Recent studies have witnessed the effectiveness of 3D convolutions on se...
research
∙
10/08/2020
MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response
Predicting clinical outcome is remarkably important but challenging. Res...
research
∙
08/24/2020
EfficientFCN: Holistically-guided Decoding for Semantic Segmentation
Both performance and efficiency are important to semantic segmentation. ...
research
∙
08/02/2020
Tensor Low-Rank Reconstruction for Semantic Segmentation
Context information plays an indispensable role in the success of semant...
research
∙
04/17/2020
Learning to Predict Context-adaptive Convolution for Semantic Segmentation
Long-range contextual information is essential for achieving high-perfor...
research
∙
07/12/2018
