Volume Calculation of Magnetic Resonance
Tissues via Image Classification
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.