title: Feature space analysis: effects of MRI protocols.
abstract: We present a method for exploring the relationship between the image segmentation results obtained by an optimal feature space method and the MRI protocols used. The steps of the work accomplished are as follows. (1) Patients with brain tumors were imaged on a 1.5 T General Electric Signa MRI System using multiple protocols (T1 and T2-weighted fast spin-echo and FLAIR). T1-weighted images were acquired before and after gadolinium injection. (2) Image volumes were co-registered, and images of a slice through the center of the tumor were selected for processing. (3) For each patient, several image sets were defined by selecting certain MR images (e.g., 4T2's+ IT1, 4T2's+FLAIR, 2T2's+ 1T1). (4) Using each image set, the optimal feature space was generated and images were segmented into normal tissues and different tumor zones. (5) Segmentation results obtained using the different MRI sets were compared. Based on the analysis results from 27 image sets, we found that the locations of the clusters for the tumor zones and their corresponding regions in the image domain changed as a function of the MR images (MRI protocols) used. However, the segmentation results for the total lesion and normal tissues remained relatively unchanged.
authors.affiliation: Department of Diagnostic Radiology, Henry Ford Health System, Detroit, Michigan 48202, USA. hamids@rad.hfh.edu
authors.forename: H
authors.initials: H
authors.lastname: Soltanian-Zadeh
authors.forename: D J
authors.initials: DJ
authors.lastname: Peck
mesh_terms: D001932:Brain Neoplasms / Q000532:radiotherapy*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000295:instrumentation* / Q000379:methods*; D015233:Models, Statistical; D013997:Time Factors