Automated Machine Recognition of Lesions in Mri of the Breast
نویسندگان
چکیده
100 Automated machine recognition of lesions in dynamic contrast-enhanced MRI of the breast 1T.P. Harte, Ph.D., 2D.J. Lomas, M.R.C.P, F.R.C.R., 2A.K. Dixon, M.D., F.R.C.R, and 1R. Hanka, Ph.D. 1Medical Informatics Unit, University of Cambridge, Robinson Way, Cambridge CB2 2SR; and 2Department of Radiology, Addenbrooke's Hospital and the University of Cambridge, Cambridge CB2 2QQ. Abstract| Routine analysis of enhancement during dynamic MRI of the breast is not yet very sophisticated. For example, we show that simple statistical analysis of subjectively selected regions of interest can provide misleading information. Moreover, almost all current methods fail to analyse the full extent of the large dynamic MR data sets; thus, subtleties in the intensity pro les of various tissues may go unnoticed. To obviate some of the problems encountered in such analytical techniques, we present an automated method of analysis for dynamic contrast-enhanced MRI of the breast based on feed-forward arti cial neural networks, which classi es every pixel of the data set. We suggest that the e ects of motion artefacts and partial volume imaging in dynamic MRI may be overcome by taking small neighbourhood masks about a pixel of interest, while maintaining the integrity of the data. The neural network classi er operates under real-time conditions, and can process a complete data set within minutes. Keywords|Breast, MR Imaging, neural networks.
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