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Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-fine Framework and Its Adversarial Examples
Although deep neural networks have been a dominant method for many 2D vi...
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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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Detecting Pancreatic Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer...
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Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation
The ability to detect failures and anomalies are fundamental requirement...
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End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation
Automatic segmentation of abdomen organs using medical imaging has many ...
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Thickened 2D Networks for 3D Medical Image Segmentation
There has been a debate in medical image segmentation on whether to use ...
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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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Iterative Reorganization with Weak Spatial Constraints: Solving Arbitrary Jigsaw Puzzles for Unsupervised Representation Learning
Learning visual features from unlabeled image data is an important yet c...
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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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Multi-Scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma
This paper proposes an intuitive approach to finding pancreatic ductal a...
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Joint Shape Representation and Classification for Detecting PDAC
We aim to detect pancreatic ductal adenocarcinoma (PDAC) in abdominal CT...
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Bridging the Gap Between 2D and 3D Organ Segmentation
There has been a debate on whether to use 2D or 3D deep neural networks ...
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A 3D Coarse-to-Fine Framework for Automatic Pancreas Segmentation
In this paper, we adopt 3D CNNs to segment the pancreas in CT images. Al...
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