Your Name

Education

B.S., Imaging Science, 2005 (anticipated)
Rochester Institute of Technology, Rochester, NY

A.S., Optics, 1998
Monroe Community College, Rochester, NY

Career Objective

To develop image processing techniques capable of identifying disease in the human body.

Employment

BMRI Industries, Rochester, NY. 1998-Pres
Performed image segmentation on magnetic resonance images.

Research

A Multispectral Analysis of Magnetic Resonance Images -

Multispectral tissue classification can be used in medicine to locate and diagnose disease. Several spectral regions are possible. In this study single-echo, spin-echo magnetic resonance images of axial slicees through the brain at the level of the lateral ventricles were recorded on a 1.5 Tesla imager from 20 volunteers ranging in age from 17 to 72 years. These images were used to calculate the T₁, T₂, and spin density images used for the classification. Tissue classification was performed by locating clusters of pixels in a three-dimensional (1/ T₁ - 1/ T₂ - spin density) histogram. Gray matter, white matter, cerebrospinal fluid, meninges, muscle, and adipose tissues were readily classified in magnetic resonance images of volunteers with a single set of T₁, T₂ and spin density values. Cluster characteristics, such as size, shape, and location provided information on the imaging procedure and tissue characteristics. See publication 3 for more information.

Honors

Dean's List, College of Science, Rochester Institute of Technology, Spring 1999.

Wegmans College Scholarship, Rochester, NY 1999-2000.

Publications

1. L.M. Fletcher, J.B. Barsotti, J.P. Hornak, A Multispectral Analysis of Brain Tissues, Magn. Reson. Med. 29:623-630, (1993).