Biomedical subjects

H Greenspan

Publications and source records attributed to H Greenspan.

3 recordsLinked to original sources

PubMed2002

MRI inter-slice reconstruction using super-resolution.

MRI reconstruction using super-resolution is presented and shown to improve spatial resolution in cases when spatially-selective RF pulses are used for localization. In 2-D multislice MRI, the resolution in the slice direction is often lower than the in-plane resolution. For certain diagnostic imaging applications, isotropic resolution is necessary but true 3-D acquisition methods are not practical. In this case, if the imaging volume is acquired two or more times, with small spatial shifts between acquisitions, combination of the data sets using an iterative super-resolution algorithm gives improved resolution and better edge definition in the slice-select direction. Resolution augmentation in MRI is important for visualization and early diagnosis. The method also improves the signal-to-noise efficiency of the data acquisition.

Algorithms↗

PubMed2002

Classification of lymphoproliferative disorders by spectral imaging of the nucleus.

Spectral nuclear morphometry was used for the classification of lymphocytes in lymphoproliferative disorders. May-Grunwald-Giemsa-stained blood specimens were taken from thirty patients with infectious mononucleosis, non-Hodgkin lymphoma or chronic lymphocytic leukemia, and from ten healthy individuals. Blood specimens were analyzed by spectral imaging. Seventeen distinct spectra were collected into a spectral library and a distinct pseudo color was assigned to each one of them. The library was used to scan all the cells in the database and to create a spectrally classified image of each cell. The spectral map, per cell, reveals distinct spectral-response regions in each cellular compartment, via the distinct region colors. Computational analysis of the spectral maps allows for the objective quantification of a set of parameters, or features, representing the cell. The features used in this work include the area and perimeter of the nucleus, circularity, edginess and the spectral pattern. The analysis pursued showed that each class of cells is associated with a set of unique parameters. We conclude that spectral analysis combined with feature analysis provides significant information in the analysis of lymphoproliferative disorders and may serve as an additional tool for the histopathological evaluation of disease.

Cell Division↗

PubMed2001

Evaluation of center-line extraction algorithms in quantitative coronary angiography.

Objective testing of centerline extraction accuracy in quantitative coronary angiography (QCA) algorithms is a very difficult task. Standard tools for this task are not yet available. We present a simulation tool that generates synthetic angiographic images of a single coronary artery with predetermined centerline and diameter function. This simulation tool was used creating a library of images for the objective comparison and evaluation of QCA algorithms. This technique also provides the means for understanding the relationship between the algorithms' performance and limitations and the vessel's geometrical parameters. In this paper, two algorithms are evaluated and the results are presented.

Algorithms↗