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07/06/2022
Unsupervised Domain Adaptation through Shape Modeling for Medical Image Segmentation
Shape information is a strong and valuable prior in segmenting organs in...
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02/09/2022
Learning to Bootstrap for Combating Label Noise
Deep neural networks are powerful tools for representation learning, but...
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01/04/2022
External Attention Assisted Multi-Phase Splenic Vascular Injury Segmentation with Limited Data
The spleen is one of the most commonly injured solid organs in blunt abd...
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09/23/2021
SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings
In this work, we introduce a fast and accurate method for unsupervised 3...
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06/28/2020
Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation
Although having achieved great success in medical image segmentation, de...
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05/25/2020
JSSR: A Joint Synthesis, Segmentation, and Registration System for 3D Multi-Modal Image Alignment of Large-scale Pathological CT Scans
Multi-modal image registration is a challenging problem yet important cl...
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03/18/2020
Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation
The ability to detect failures and anomalies are fundamental requirement...
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12/06/2019
Deep Distance Transform for Tubular Structure Segmentation in CT Scans
Tubular structure segmentation in medical images, e.g., segmenting vesse...
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08/21/2019
FusionNet: Incorporating Shape and Texture for Abnormality Detection in 3D Abdominal CT Scans
Automatic abnormality detection in abdominal CT scans can help doctors i...
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03/26/2019
An Alarm System For Segmentation Algorithm Based On Shape Model
It is usually hard for a learning system to predict correctly on rare ev...
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11/29/2018
3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training
We propose a novel framework, uncertainty-aware multi-view co-training (...
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04/27/2018
Joint Shape Representation and Classification for Detecting PDAC
We aim to detect pancreatic ductal adenocarcinoma (PDAC) in abdominal CT...
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04/02/2018