Dorin Comaniciu

TL;DR: A probabilistic framework for component-based automatic detection and tracking of objects in video using spatio-temporal two-layer graphical models, where each node corresponds to an object or component of an object at a given time, and the edges correspond to learned spatial and temporal constraints.

TL;DR: A semi‐automated framework that combines machine learning image analysis with geometrical and biomechanical models to build a patient‐specific mitral valve representation that incorporates image‐derived material properties is proposed and developed.

TL;DR: A robust algorithm is proposed for automatically tracing the envelopes of mitral valve inflow Doppler spectra, which exhibit a large amount of variations in envelope shape and image appearance due to various disease conditions, patient/sonographer/instrument differences, etc.

TL;DR: An automatic method to estimate the regional 3D myocardial mechanics on ultrasound images by recovering the 3D non-rigid deformation of the myocardium is proposed and achieves high speed performance of less than 1 second per frame for volumetric ultrasound data.

TL;DR: In this article, a method for selecting a subject for a clinical study includes providing a criteria for selecting one or more subjects from a database, performing a content based similarity search of the database to retrieve subjects who meet the selection criteria, presenting the selected subjects to a user, and receiving user feedback regarding the selected subject.