Computer-aided detection of metastatic brain tumors using automated three-dimensional template matching
dc.contributor.author | Ambrosini, Robert D. | en_US |
dc.contributor.author | Wang, Peng | en_US |
dc.contributor.author | O'Dell, Walter G. | en_US |
dc.date.accessioned | 2010-01-05T15:11:02Z | |
dc.date.available | 2011-03-01T16:26:41Z | en_US |
dc.date.issued | 2010-01 | en_US |
dc.identifier.citation | Ambrosini, Robert D.; Wang, Peng; O'Dell, Walter G. (2010). "Computer-aided detection of metastatic brain tumors using automated three-dimensional template matching." Journal of Magnetic Resonance Imaging 31(1): 85-93. <http://hdl.handle.net/2027.42/64548> | en_US |
dc.identifier.issn | 1053-1807 | en_US |
dc.identifier.issn | 1522-2586 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/64548 | |
dc.description.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. | en_US |
dc.format.extent | 283146 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.publisher | Wiley Subscription Services, Inc., A Wiley Company | en_US |
dc.subject.other | Life and Medical Sciences | en_US |
dc.subject.other | Imaging | en_US |
dc.title | Computer-aided detection of metastatic brain tumors using automated three-dimensional template matching | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Medicine (General) | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA | en_US |
dc.contributor.affiliationother | Department of Biomedical Engineering, University of Rochester, Rochester, New York, USA | en_US |
dc.contributor.affiliationother | Department of Radiation Oncology, University of Rochester, Rochester, New York, USA ; 601 Elmwood Avenue, University of Rochester, Box 647, Rochester, NY 14642-8647 | en_US |
dc.identifier.pmid | 20027576 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/64548/1/22009_ftp.pdf | |
dc.identifier.doi | 10.1002/jmri.22009 | en_US |
dc.identifier.source | Journal of Magnetic Resonance Imaging | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.