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Given a set of training shapes and an input image with a shape similar to some of the elements in the training set, this poster introduces a new implicit kernel sparse model with a twofold goal. First, to obtain an implicit kernel sparse neighbor based combination that best represents the object. Second, to accurately segment the object taking into accounts both the high-level implicit kernel presentation and the low-level image information.

A signal based algorithm resulting in increased depth resolution is presented for medical ultrasound. It relies on multiple foci beamforming that is enabled by current ultrasound imaging systems. The concept stems from optical microscopy and is translated here into ultrasound using the Field II simulation software. A 7 MHz linear transducer is used to scan a single point scatterer phantom that can move in the axial direction.