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Dergiler / Istanbul University Journal of Electrical and Electronics Engineering / 2007 / Cilt: 7 - Sayı: 2

3D colonic polyp detection in CT images using template matching

Serhat ÖZEKES
Sayfa
411–418
Yayın Tarihi
2022-10-18
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

When the results were comparedwith the reviews of the radiologists, it was seen that the system achieved 92.3% sensitivity with 0.84FP regions per polyp.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In this paper we present a computer aided detection (CAD) system for colonic polyp detection incomputed tomography (CT) images.
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Temel Bulgular & Veri:After extracting the colon region, searching with 3D semi-spherical polyp template wasperformed to detect the polyps.
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Sonuç & Katkı:When the results were comparedwith the reviews of the radiologists, it was seen that the system achieved 92.3% sensitivity with 0.84FP regions per polyp.
🔬Tür:Literatür & Derleme Çalışması
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

In this paper we present a computer aided detection (CAD) system for colonic polyp detection incomputed tomography (CT) images. Here, the segmentation of the colon region was performed inthree steps which are thresholding, labeling and analyzing the shape morphologies using decisionrules. After extracting the colon region, searching with 3D semi-spherical polyp template wasperformed to detect the polyps. Because the polyps can appear in all possible orientations on thecolon wall, 3D rotations were performed during the search. The similarity was measured usingconvolution operation. The performance of the system was evaluated using a test set containing 20cases having 13 polyps which were marked by expert radiologists. When the results were comparedwith the reviews of the radiologists, it was seen that the system achieved 92.3% sensitivity with 0.84FP regions per polyp.

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Bu Makaleye Atıf Yap

ÖZEKES, S. (2022). 3D colonic polyp detection in CT images using template matching. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 7 - Sayı: 2, 411–418. https://ajindex.com/articles/543779

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  1. Mayor S., “Single flexible sigmoidoscopy screening to prevent colorectal cancer: baseline findings of a UK multicentre randomised trial”, The Lancet, Vol 359, April 13 2002, pp. 1291 – 1300 [2] Daniel C., Johnson and Abraham H. Dachman, “CT Colonography: The Next Colon Screening Examination?”, Radiology 2000 216: 331-341. [3] Pickhardt P. J., Choi J. R., Hwang I., Butler J. A., Puckett M. L., Hildebrandt H. A., Wong R. K., Nugent P. A., Mysliwiec P. A., and Schindler W. R., "Computed Tomographic Virtual Colonoscopy to Screen for Colorectal Neoplasia in Asymptomatic Adults," The New England Journal of Medicine, vol. 349, pp. 2191, 2003. [4] Yoshida H., Nppi J., “Three-Dimensional Computer- Aided Diagnosis Scheme for Detection of Colonic Polyps”, Trans. on Medical Imaging, vol. 20, no. 12, 2001. [5] Vining D. J., Ge Y., Ahn D. K., Stelts D. R., “Virtual colonoscopy with computer-assisted polyp detection”, Computer-Aided Diagnosis in Medical Imaging. Address: Amsterdam, Netherlands: Elsevier Science B.V., pp. 445-452 1999. [6] Summers R.M., Johnson C.D., Pusanik L.M., Malley J.D., Youssef A.M., Reed J.E., “Automated polyp detection at CT colonography: Feasibility assessment in a human population,” Radiology, vol. 219, pp. 51–59, 2001. [7] Kiss G., Van J., Thomeer M., Suetens P., Marchal G., “Computer-aided diagnosis in virtual colonography via combination of surface normal and sphere fitting methods,” European Radiology, vol. 12, pp. 77–81, 2002. [8] Yoshida H., Masutani Y., MacEneaney P., Rubin D. T., Dachman A. H., “Computerized detection of colonic polyps at CT colonography on the basis of volumetric features: Pilot study”, Radiology, vol. 222, pp. 327-336, 2002. [9] Paik D.S., Beaulieu C.F., Rubin G.D., Acar B., Jeffrey R.B., Yee J., Dey J., Napel S., “Surface normal overlap: a computeraided detection algorithm with application to colonic polyps and lung nodules in helical CT”, IEEE Trans Med Imaging, 23(6) pp. 661-75, 2004. [10] http://nova.nlm.nih.gov/WRAMC [11] Hounsfield G.N., “Computed medical imaging”, Med Phys., vol. 7, pp. 283-90, (1980). [12] Wyatt C.L., Ge Y., Vining D.J., “Automatic Segmentation of Colon for Virtual Colonoscopy”, Computrized medical Imaging and graphics,Vol. 24, 2000(1-9). [13] Masutani Y., Yoshida H., MaacEnearney P., Dachman A.,”Automated Segmentation of Colonic Walls for Computerized detection of Polypsin CT Colonography”, Journal of Computer Assisted Tomography, Vol. 25(4), july/Agust 2001, pp 629-638 [14] Perry J., e