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
∙
07/20/2023
Parse and Recall: Towards Accurate Lung Nodule Malignancy Prediction like Radiologists
Lung cancer is a leading cause of death worldwide and early screening is...
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
∙
07/19/2020
E^2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans
Developing an effective liver and liver tumor segmentation model from CT...
research
∙
07/14/2020
Cross-Domain Medical Image Translation by Shared Latent Gaussian Mixture Model
Current deep learning based segmentation models often generalize poorly ...
research
∙
02/08/2020
Bone Suppression on Chest Radiographs With Adversarial Learning
Dual-energy (DE) chest radiography provides the capability of selectivel...
research
∙
08/21/2019
TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays
In this work, we exploit the unsupervised domain adaptation problem for ...
research
∙
04/19/2019
XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation
This paper proposes a novel framework for lung segmentation in chest X-r...
research
∙
03/05/2019
Abnormal Chest X-ray Identification With Generative Adversarial One-Class Classifier
Being one of the most common diagnostic imaging tests, chest radiography...
research
∙
01/18/2019
ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining
Automatic lesion detection from computed tomography (CT) scans is an imp...
research
∙
07/19/2018
Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs
In this work, we exploit the task of joint classification and weakly sup...
research
∙
01/09/2018
Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection
Deep CNN-based object detection systems have achieved remarkable success...
research
∙
04/13/2017
