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Biomedical subjects

M B Merickel

Publications and source records attributed to M B Merickel.

5 recordsLinked to original sources
PubMedDate not supplied

Image analysis and quantification of atherosclerosis using MRI.

This paper describes an image processing, pattern recognition, and computer graphics system for the noninvasive identification and evaluation of atherosclerosis using multidimensional Magnetic Resonance Imaging (MRI). Particular emphasis has been placed on the problem of developing a pattern recognition system for noninvasively identifying the different plaque classes involved in atherosclerosis using minimal a priori information. This pattern recognition technique involves an extension of the ISODATA clustering algorithm to include an information theoretic criterion (Consistent Akaike Information Criterion) to provide a measure of the fit of the cluster composition at a particular iteration to the actual data. A rapid 3-D display system is also described for the simultaneous display of multiple data classes resulting from the tissue identification process. This work demonstrates the feasibility of developing a "high information content" display which will aid in the diagnosis and analysis of the atherosclerotic disease process. Such capability will permit detailed and quantitative studies to assess the effectiveness of therapies, such as drug, exercise, and dietary regimens.

Algorithms↗
PubMedDate not supplied

Breast lesion discrimination using statistical analysis and shape measures on magnetic resonance imagery.

Magnetic resonance images of intact human breast tissue are evaluated using statistical measures and shape analysis. In this paper, the Mahalanobis distance measurement and a related F-statistical value demonstrate that breast lesions are statistically separable from normal breast tissue. The minimum set of parameters to provide first order statistical separability between fibroadenomas, cysts, and carcinomas are T1-weighted, T2-weighted, and Dixon opposed pulse sequences. Tumor shape is quantified by development of a compactness measure and a spatial frequency analysis of the lesion boundary. Malignant lesions are shown to be separable from benign lesions based on quantitative shape measures.

Adenofibroma↗
PubMedDate not supplied

Applications of hierarchical image segmentation techniques: aorta segmentation.

The segmentation of objects from complex images is difficult due to indistinct boundaries between objects and similarity of objects. We have used a hierarchical segmentation approach to accurately distinguish between objects and identify the corresponding boundaries. This approach has been used successfully to extract the aorta from transverse magnetic resonance (MR) images of the abdomen. The procedure to segment the abdominal aorta involves three progressive steps: aorta detection, aorta extraction, and estimation of the aorta wall boundary. Comparison of hierarchical segmentation techniques with single-step segmentation methods (e.g., region-growing, edge-detection) shows that hierarchical segmentation yields more reliable results.

Aorta, Abdominal↗