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

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...

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Bibliographic Details
Published in:Journal of magnetic resonance imaging 2010-01, Vol.31 (1), p.85-93
Main Authors: Ambrosini, Robert D., Wang, Peng, O'Dell, Walter G.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
brain
Brain Neoplasms - diagnosis
Brain Neoplasms - secondary
CAD
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Imaging, Three-Dimensional - methods
Magnetic resonance imaging
object detection
Pattern Recognition, Automated - methods
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique
tumors
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Summary: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.
ISSN:1053-1807
1522-2586
DOI:10.1002/jmri.22009