Biomedical subjects

Hemant D Tagare

Publications and source records attributed to Hemant D Tagare.

3 recordsLinked to original sources

PubMed2006

Evaluation of four probability distribution models for speckle in clinical cardiac ultrasound images.

Segmenting cardiac ultrasound images requires a model for the statistics of speckle in the images. Although the statistics of speckle are well understood for the raw transducer signal, the statistics of speckle in the image are not. This paper evaluates simple empirical models for first-order statistics for the distribution of gray levels in speckle. The models are created by analyzing over 100 images obtained from commercial ultrasound machines in clinical settings. The data in the images suggests a unimodal scalable family of distributions as a plausible model. Four families of distributions (Gamma, Weibull, Normal, and Log-normal) are compared with the data using goodness-of-fit and misclassification tests. Attention is devoted to the analysis of artifacts in images and to the choice of goodness-of-fit and misclassification tests. The distribution of parameters of one of the models is investigated and priors for the distribution are suggested.

Algorithms↗

PubMed2005

Optimal embedding for shape indexing in medical image databases.

Fast retrieval using organ shapes is crucial in medical image databases since shape is a clinically prominent feature. In this paper, we propose that 2-D shapes in medical image databases can be indexed by embedding them into a vector space and using efficient vector space indexing. An optimal shape space embedding is proposed for this purpose. Experimental results of indexing vertebral shapes in the NHANES II database are presented. The results show that vector space indexing following embedding gives superior performance than metric indexing.

Databases, Factual↗

PubMed2003

Tunnelling descent: a new algorithm for active contour segmentation of ultrasound images.

The presence of speckle in ultrasound images makes it hard to segment them using active contours. Speckle causes the energy function of the active contours to have many local minima, and the gradient descent procedure used for evolving the contour gets trapped in these minima. A new algorithm, called tunnelling descent, is proposed in this paper for evolving active contours. Tunnelling descent can jump out of many of the local minima that gradient descent gets trapped in. Experimental results with 70 short axis cardiac ultrasound images show that tunnelling descent has no trouble finding the blood-tissue boundary (the endocardium). This holds irrespective of whether tunnelling descent is initialized in blood or tissue.

Algorithms↗