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Proceedings Paper

Comparison of automatic time curve selection methods for breast MR CAD
Author(s): Tanya L. Niemeyer; Chris Wood; Keith C. Stegbauer; Justin P. Smith
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Paper Abstract

Breast MR is being employed to detect, diagnose, and stage breast cancer. With a breast MR study, areas that exhibit rapid uptake of contrast followed by washout behavior have been shown to be indicative of malignant tissue. The most common way to display this temporal information is with a time versus percent enhancement curve that plots the enhancement of the tissue for each series relative to a baseline or pre contrast series. The generation of time curves is commonly done using manual methods, but could easily be automated by a computer to reduce user variability. The information obtained by the time curve can then be used for computer assisted analysis of suspicious areas. We compare two methods for the automated detection of such time curves for 42 malignant lesions. The first method is a previously published technique which finds the highest enhancing 3x3 area of a lesion to generate a curve. The second method is a new hierarchical search that examines end time point behavior in combination with enhancement to find an optimal curve location. The two methods for curve generation are examined in their ability to produce a washout type curve, which has a greater likelihood of being malignant than curves that continue to enhance. The time curves found using highest percent enhancement method showed washout in 52 percent (22/42) of lesions. Using the hierarchical search algorithm, 90 percent (38/42) of lesions showed washout type curves

Paper Details

Date Published: 12 May 2004
PDF: 6 pages
Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.535992
Show Author Affiliations
Tanya L. Niemeyer, Confirma, Inc. (United States)
Chris Wood, Confirma, Inc. (United States)
Keith C. Stegbauer, Confirma, Inc. (United States)
Justin P. Smith, Confirma, Inc. (United States)
First Hill Diagnostic Imaging (United States)


Published in SPIE Proceedings Vol. 5370:
Medical Imaging 2004: Image Processing
J. Michael Fitzpatrick; Milan Sonka, Editor(s)

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