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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...
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08/30/2023
SAM-Med2D
The Segment Anything Model (SAM) represents a state-of-the-art research ...
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07/26/2023
Artifact Restoration in Histology Images with Diffusion Probabilistic Models
Histological whole slide images (WSIs) can be usually compromised by art...
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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...
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03/10/2023
Generative Model Based Noise Robust Training for Unsupervised Domain Adaptation
Target domain pseudo-labelling has shown effectiveness in unsupervised d...
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03/08/2023
FCN+: Global Receptive Convolution Makes FCN Great Again
Fully convolutional network (FCN) is a seminal work for semantic segment...
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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 ...
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09/06/2022
An evaluation of U-Net in Renal Structure Segmentation
Renal structure segmentation from computed tomography angiography (CTA) ...
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05/17/2022
Vision Transformer Adapter for Dense Predictions
This work investigates a simple yet powerful adapter for Vision Transfor...
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03/23/2022
StructToken : Rethinking Semantic Segmentation with Structural Prior
In this paper, we present structure token (StructToken), a new paradigm ...
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03/09/2022
Dynamic Instance Domain Adaptation
Most existing studies on unsupervised domain adaptation (UDA) assume tha...
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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...
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09/26/2021
Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation
Recent studies have witnessed the effectiveness of 3D convolutions on se...
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10/08/2020
MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response
Predicting clinical outcome is remarkably important but challenging. Res...
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08/24/2020
EfficientFCN: Holistically-guided Decoding for Semantic Segmentation
Both performance and efficiency are important to semantic segmentation. ...
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08/02/2020
Tensor Low-Rank Reconstruction for Semantic Segmentation
Context information plays an indispensable role in the success of semant...
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04/17/2020
Learning to Predict Context-adaptive Convolution for Semantic Segmentation
Long-range contextual information is essential for achieving high-perfor...
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07/12/2018