[CSEE-colloq] CSEE Colloquium - Shih-Yu Chen on Volume Calculation of Magnetic Resonance Tissues, 1pm Fri 10/5, UMBC

[Yaacov Yesha]

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From: Tim Finin <finin at cs.umbc.edu>
Date: Tue, Sep 25, 2012 at 9:04 PM
Subject: [Csee-faculty-tt] [CSEE-colloq] talk: Volume Calculation of
Magnetic Resonance Tissues, 1pm Fri 10/5, UMBC
To: csee-colloquium-out at cs.umbc.edu


                        -- CSEE Colloquium --

               Volume Calculation of Magnetic Resonance
                   Tissues Via Image Classification

                             Shih-Yu Chen
         Remote Sensing Signal & Image Processing Laboratory
           UMBC Computer Science and Electrical Engineering

                1:00pm Friday 5 October 2012, ITE 227

Magnetic resonance (MR) tissue volume calculation is very important in
medical diagnosis. A general approach is to first perform image
classification of desired tissue substances slice by slice and then
calculate tissue volumes via classified data samples in each slice.
Two issues are generally involved; (1) selection of training samples
which are slice-dependent, i.e., each slice requires its own specific
training samples and (2) classification which must be carried out
slice by slice individually because training samples obtained from one
slice are not necessarily applicable to another. We develop a volume
sphering analysis (VSA) approach which can process all MR image slices
as one single image cube to calculate tissue volumes via image
classification using only one set of training samples that is obtained
from a single image slice. The proposed VSA using one set of training
samples not only performs comparably to that using training samples
specifically selected for individual image slices, but also saves
significant amounts of selecting training samples and computing time.

Shih-Yu Chen received the BS degree in Electrical Engineering from
Da-Yeh University in 2005, and the MS EE degree from National Chung
Hsing University in 2010. He is currently a PhD (EE) student at
UMBC. Mr. Chen's research interest includes medical image, remote
sensing image and vital sign signal processing.

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