– Automated CT Liver Volumetry by Use of Three-Dimensional Fast-Marching and Level-Set Segmentation

– A CAD Utilizing 3D Massive-Training ANNs for Detection of Flat Lesions in CT Colonography in a Large Multicenter Clinical Trial

– Polyp Detection in CT Colonography: Performance of a CAD Scheme Incorporating 3D MTANNs on False-Negative Polyps in a Multicenter Clinical Trial

– Ensemble Training for a Mixture of Expert 3D MTANNs for Eliminating Multiple False-Positive Sources in CAD for Polyp Detection in CT Colonography

– Eliminating Multiple False-Positive Sources in CAD for Polyp Detection in CT Colonography by Means of a Mixture of Expert 3D Massive-Training Artificial Neural Networks

– Reduction of False Positives in Computer-Aided Detection of Polyps in CT Colonography Using a Massive-Training Artificial Neural Network (MTANN): Suppression of Rectal Tubes

– Computerized Detection of Lung Nodules in Low-Dose CT, Part I: Basic Principle of Massive-Training Artificial Neural Network (MTANN) for Reduction of False Positives

– Computerized Detection of Lung Nodules in Low-Dose CT, Part II: Usefulness of Multiple Massive-Training Artificial Neural Networks (Multi-MTANNs)

– Massive-Training Artificial Neural Network (MTANN) Trained with a Small Number of Cases for Enhancement of Nodules and Suppression of Vessels in Thoracic CT: Phantom Experiments

– Reduction of False Positives in a CAD Scheme for Detection of Lung Nodules on MDCT by Use of 3D Massive-Training Artificial Neural Network

– Computer-aided Diagnostic Scheme for Distinction between Benign and Malignant Nodules in Thoracic Low-Dose CT by Use of a Massive-Training Artificial Neural Network

– False-Positive Reduction in Computer-Aided Diagnostic Scheme for Detection of Nodules on Chest Radiographs by Means of Massive-Training Artificial Neural Network (MTANN)

– Computer-Aided Diagnostic System for Detection and Estimation of Coronary Artery Stenosis by Use of a Linear-Output Artificial Neural Network

– Extraction of Left Ventricular Contours from Left Ventriculograms by Means of a Neural Edge Detector

– Robust Algorithm for Tracing Vessels in Coronary Angiography