Sparse Dimensionality Reduction for Medical Imaging

The complex and high-dimensional nature of medical images makes them difficult to incorporate into traditional linear model-based statistical analysis.  One way of simplifying analysis of medical images is to use a dimensionality reduction technique.  We designed a dimensionality reduction technique … Continue reading


We have been developing a framework to incorporate ITK and ANTs-based image processing methods into the R programming language to allow for interactive statistical analysis of medical images.  R provides the most complete and current selection of statistical tools, including … Continue reading

Prediction of stress distributions on image-derived models of the mitral leaflets

An integrated methodology for imaging, segmenting, modeling, and deriving computationally-predicted pressure-derived mitral leaflet stresses is presented and points the way towards intraoperative and periprocedural guidance from morphometric and stress modeling of the mitral valve. In vivo human mitral valves are … Continue reading

Fully automated segmentation of the mitral leaflets using multi-atlas label fusion and deformable medial modeling

Comprehensive visual and quantitative analysis of in vivo human mitral valve morphology is central to the diagnosis and surgical treatment of mitral valve disease. Real-time 3D transesophageal echocardiography (3D TEE) is a practical, highly informative imaging modality for examining the … Continue reading

Semi-automated segmentation of the mitral leafelts in 3D echocardiographic images

Precise 3D modeling of the mitral valve has the potential to improve our understanding of valve morphology, particularly in the setting of mitral regurgitation (MR). Toward this goal, we have developed a user-initialized algorithm for reconstructing valve geometry from transesophageal 3D echocardiographic (3DE) … Continue reading