Quick Detection of Brain Tumors and Edemas: A Bounding Box Method Using Symmetry
A signifiÂcant medical informatics task is indexing patient databases according to size, location, and other characteristics of brain tumors and edemas, possibly based on magnetic resonance (MR) imagery. This
requires segmenting tumors and edemas within images from different MR modalities. To date, automated brain tumor or edema segmentation from MR modalities remains a challenging, computationally intensive task. In this paper, we propose a novel automated, fast, and approximate segmentation technique. The input is a patient study consisting of a set of MR slices, and its output is a subset of the slices that include axis-parallel boxes that circumscribe the tumors. Our approach is based on an unsupervised change detection method that searches for the most dissimilar region (axis-parallel bounding boxes) between the left and the right halves of a brain in an axial view MR slice. This change detection process
uses a novel score function based on Bhattacharya coefficient computed with gray level intensity histograms. We prove that this score function admits a very fast (linear in image height and width) search
to locate the bounding box. The average dice coefficient for localizing brain tumors and edemas, over
ten patient studies, are 0.57 and 0.52, respectively, which significantly exceeds the scores for two other
competitive region-based bounding box techniques.
Citation
B. Saha,
N. Ray,
R. Greiner,
A. Murtha,
H. Zhang.
"Quick Detection of Brain Tumors and Edemas: A Bounding Box Method Using Symmetry".
Computerized Medical Imaging and Graphics, August 2011.
Keywords: |
NMR, medical imaging, Brain tumor, medical informatics |
Category: |
In Journal |
Web Links: |
URL |
BibTeX
@article{Saha+al:11,
author = {B Nath Saha and Nilanjan Ray and Russ Greiner and Albert Murtha and
Hong Zhang},
title = {Quick Detection of Brain Tumors and Edemas: A Bounding Box Method
Using Symmetry},
journal = {Computerized Medical Imaging and Graphics},
year = 2011,
}
Last Updated: October 01, 2013
Submitted by Russ Greiner