Combining multiparametric MRI with receptor information to optimize prediction of pathologic response to neoadjuvant therapy in breast cancer: preliminary results.

Pathologic complete response following neoadjuvant therapy (NAT) is used as a short-term surrogate marker of eventual outcome in patients with breast cancer. Analyzing voxel-level heterogeneity in MRI-derived parametric maps, obtained before and after the first cycle of NAT ([Formula: see text]), in conjunction with receptor status, may improve the predictive accuracy of tumor response to NAT. Toward that end, we incorporated two MRI-derived parameters, the apparent diffusion coefficient and efflux rate constant, with receptor status in a logistic ridge-regression model.

Prediction of imbibition in unconsolidated granular materials.

A new way of modeling imbibition is proposed in this paper. It combines two elements. One is a physically consistent, dynamic criterion for the imbibition of an individual pore originally suggested by Melrose (SPEJ (November 1965) 259-271).

Volumetric feature extraction and visualization of tomographic molecular imaging.

Electron tomography is useful for studying large macromolecular complex within their cellular context. The associate problems include crowding and complexity. Data exploration and 3D visualization of complexes require rendering of tomograms as well as extraction of all features of interest.