Computer-aided detection of metastatic brain tumors using automated three-dimensional template matching

✍ Scribed by Robert D. Ambrosini; Peng Wang; Walter G. O'Dell

• Publisher: John Wiley and Sons
• Year: 2009
• Tongue: English
• Weight: 274 KB
• Volume: 31
• Category: Article
• ISSN: 1053-1807
• DOI: 10.1002/jmri.22009

✦ Synopsis

Abstract

Purpose:

To demonstrate the efficacy of an automated three‐dimensional (3D) template matching‐based algorithm in detecting brain metastases on conventional MR scans and the potential of our algorithm to be developed into a computer‐aided detection tool that will allow radiologists to maintain a high level of detection sensitivity while reducing image reading time.

Materials and Methods:

Spherical tumor appearance models were created to match the expected geometry of brain metastases while accounting for partial volume effects and offsets due to the cut of MRI sampling planes. A 3D normalized cross‐correlation coefficient was calculated between the brain volume and spherical templates of varying radii using a fast frequency domain algorithm to identify likely positions of brain metastases.

Results:

Algorithm parameters were optimized on training datasets, and then data were collected on 22 patient datasets containing 79 total brain metastases producing a sensitivity of 89.9% with a false positive rate of 0.22 per image slice when restricted to the brain mass.

Conclusion:

Study results demonstrate that the 3D template matching‐based method can be an effective, fast, and accurate approach that could serve as a useful tool for assisting radiologists in providing earlier and more definitive diagnoses of metastases within the brain. J. Magn. Reson. Imaging 2010;31:85–93. © 2009 Wiley‐Liss, Inc.