research
∙
08/01/2023
Improved Prognostic Prediction of Pancreatic Cancer Using Multi-Phase CT by Integrating Neural Distance and Texture-Aware Transformer
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer in whi...
share
research
∙
07/17/2023
Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network
Liver tumor segmentation and classification are important tasks in compu...
research
∙
07/10/2023
Cluster-Induced Mask Transformers for Effective Opportunistic Gastric Cancer Screening on Non-contrast CT Scans
Gastric cancer is the third leading cause of cancer-related mortality wo...
research
∙
04/01/2023
Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization
Real-world medical image segmentation has tremendous long-tailed complex...
research
∙
03/02/2023
Meta-information-aware Dual-path Transformer for Differential Diagnosis of Multi-type Pancreatic Lesions in Multi-phase CT
Pancreatic cancer is one of the leading causes of cancer-related death. ...
research
∙
01/28/2023
Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans
Human readers or radiologists routinely perform full-body multi-organ mu...
research
∙
06/04/2021
Glance-and-Gaze Vision Transformer
Recently, there emerges a series of vision Transformers, which show supe...
research
∙
04/20/2021
Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation
Federated learning (FL) enables collaborative model training while prese...
research
∙
10/29/2020
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...
research
∙
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...
research
∙
03/18/2020
Detecting Pancreatic Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer...
research
∙
03/18/2020
Synthesize then Compare: Detecting Failures and Anomalies for Semantic Segmentation
The ability to detect failures and anomalies are fundamental requirement...
research
∙
10/15/2019
End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation
Automatic segmentation of abdomen organs using medical imaging has many ...
research
∙
04/02/2019
Thickened 2D Networks for 3D Medical Image Segmentation
There has been a debate in medical image segmentation on whether to use ...
research
∙
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...
research
∙
12/02/2018
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...
research
∙
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 (...
research
∙
07/09/2018
Multi-Scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma
This paper proposes an intuitive approach to finding pancreatic ductal a...
research
∙
04/27/2018
Joint Shape Representation and Classification for Detecting PDAC
We aim to detect pancreatic ductal adenocarcinoma (PDAC) in abdominal CT...
research
∙
04/02/2018
Bridging the Gap Between 2D and 3D Organ Segmentation
There has been a debate on whether to use 2D or 3D deep neural networks ...
research
∙
12/01/2017