47 citations · 52 across the 4 of their papers we have counts for
4 papers
Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation
Hoo-Chang Shin, Le Lu, Lauren Kim +3
Despite tremendous progress in computer vision, there has not been an attempt for machine learning on very large-scale medical image databases. We present an interleaved text/image…
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-…