TY - JOUR
T1 - Edge displacement field-based classification for improved detection of polyps in CT colonography
AU - Acar, Burak
AU - Beaulieu, Christopher F.
AU - Göktürk, Salih B.
AU - Tomasi, Carlo
AU - Paik, David S.
AU - Jeffrey, R. Brooke
AU - Yee, Judy
AU - Napel, Sandy
N1 - Funding Information:
Manuscript received July 1, 2001; revised July 29, 2002. This work was supported in part by the National Institutes of Health under Grant 1R01 CA72023 and in part by grants from The Lucas Foundation, The Packard Foundation, and The Phil N. Allen Trust. The Associate Editor responsible for coordinating the review of this paper and recommending its publication was M. Giger. Asterisk indicates corresponding author. *B. Acar is with the Department of Radiology, LUCAS MRS Center, 3D Laboratory, Stanford University, Stanford, CA 94305 USA (e-mail: bacar@ stanford.edu).
PY - 2002/12
Y1 - 2002/12
N2 - Colorectal cancer can easily be prevented provided that the precursors to tumors, small colonic polyps, are detected and removed. Currently, the only definitive examination of the colon is fiber-optic colonoscopy, which is invasive and expensive. Computed tomographic colonography (CTC) is potentially a less costly and less invasive alternative to FOC. It would be desirable to have computer-aided detection (CAD) algorithms to examine the large amount of data CTC provides. Most current CAD algorithms have high false positive rates at the required sensitivity levels. We developed and evaluated a postprocessing algorithm to decrease the false positive rate of such a CAD method without sacrificing sensitivity. Our method attempts to model the way a radiologist recognizes a polyp while scrolling a cross-sectional plane through three-dimensional computed tomography data by classification of the changes in the location of the edges in the two-dimensional plane. We performed a tenfold cross-validation study to assess its performance using sensitivity/specificity analysis on data from 48 patients. The mean specificity over all experiments increased from 0.19 (0.35) to 0.47 (0.56) for a sensitivity of 1.00 (0.95).
AB - Colorectal cancer can easily be prevented provided that the precursors to tumors, small colonic polyps, are detected and removed. Currently, the only definitive examination of the colon is fiber-optic colonoscopy, which is invasive and expensive. Computed tomographic colonography (CTC) is potentially a less costly and less invasive alternative to FOC. It would be desirable to have computer-aided detection (CAD) algorithms to examine the large amount of data CTC provides. Most current CAD algorithms have high false positive rates at the required sensitivity levels. We developed and evaluated a postprocessing algorithm to decrease the false positive rate of such a CAD method without sacrificing sensitivity. Our method attempts to model the way a radiologist recognizes a polyp while scrolling a cross-sectional plane through three-dimensional computed tomography data by classification of the changes in the location of the edges in the two-dimensional plane. We performed a tenfold cross-validation study to assess its performance using sensitivity/specificity analysis on data from 48 patients. The mean specificity over all experiments increased from 0.19 (0.35) to 0.47 (0.56) for a sensitivity of 1.00 (0.95).
KW - Computed tomographic colonography (CTC)
KW - Computer-aided diagnosis
KW - Edge displacement fields (EDFs)
KW - Fiber-optic colonoscopy (FOC)
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U2 - 10.1109/TMI.2002.806405
DO - 10.1109/TMI.2002.806405
M3 - Article
C2 - 12588030
AN - SCOPUS:0037004760
SN - 0278-0062
VL - 21
SP - 1461
EP - 1467
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
IS - 12
ER -