10 citations · 16 across the 6 of their papers we have counts for
6 papers
Radiotherapy Target Contouring with Convolutional Gated Graph Neural Network
Chun-Hung Chao, Yen-Chi Cheng, Hsien-Tzu Cheng +5
Tomography medical imaging is essential in the clinical workflow of modern cancer radiotherapy. Radiation oncologists identify cancerous tissues, applying delineation on treatment…
Holistic Interstitial Lung Disease Detection using Deep Convolutional Neural Networks: Multi-label Learning and Unordered Pooling
Mingchen Gao, Ziyue Xu, Le Lu +3
Accurately predicting and detecting interstitial lung disease (ILD) patterns given any computed tomography (CT) slice without any pre-processing prerequisites, such as manually del…
2D View Aggregation for Lymph Node Detection Using a Shallow Hierarchy of Linear Classifiers
Ari Seff, Le Lu, Kevin M. Cherry +6
Enlarged lymph nodes (LNs) can provide important information for cancer diagnosis, staging, and measuring treatment reactions, making automated detection a highly sought goal. In t…
A Bottom-Up Approach for Automatic Pancreas Segmentation in Abdominal CT Scans
Amal Farag, Le Lu, Evrim Turkbey +2
Organ segmentation is a prerequisite for a computer-aided diagnosis (CAD) system to detect pathologies and perform quantitative analysis. For anatomically high-variability abdomina…
Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications
Holger R. Roth, Jianhua Yao, Le Lu +3
Automated detection of sclerotic metastases (bone lesions) in Computed Tomography (CT) images has potential to be an important tool in clinical practice and research. State-of-the-…
Coarse-to-Fine Classification via Parametric and Nonparametric Models for Computer-Aided Diagnosis
Meizhu Liu, Le Lu, Xiaojing Ye +1
Classification is one of the core problems in Computer-Aided Diagnosis (CAD), targeting for early cancer detection using 3D medical imaging interpretation. High detection sensitivi…