Browse > Article

Automatic Detection of Kidney Tumor from Abdominal CT Scans  

김도연 (충남대학교 컴퓨터공학과)
노승무 (충남대학교 일반외과)
조준식 (충남대학교 진단방사선과)
김종철 (충남대학교 진단방사선과)
박종원 (충남대학교 정보통신공학과)
Publication Information
Journal of KIISE:Software and Applications / v.29, no.11, 2002 , pp. 803-808 More about this Journal
Abstract
This paper describes automatic methods for detection of kidney and kidney tumor on abdominal CT scans. The abdominal CT images were digitalized using a film digitizer and a gray-level threshold method was used to segment the kidney. Based on texture analysis results, which were perform on sample images of kidney tumors, SEED region of kidney tumor was selected as result of homogeneity test. The average and standard deviation, which are representative statistical moments, were used to as an acceptance criteria for homogeneous test. Region growing method was used to segment the kidney tumor from the center pixel of selected SEED region using a gray-level value as an acceptance criteria for homogeneity test. These method were applied to 113 images of 9 cases, which were scanned by GE Hispeed Advantage CT scanner and digitalized by Lumisvs LS-40 film digitizer. The sensitivity was 85% and there was no false-positive results.
Keywords
Medical Image Processing; CAD(Computer Aided Diagnosis); Kidney Tumor; Texture Analysis; Region Growing;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Giger ML, Bae KT, MacMahon H, 'Computerized Detection of Pulmonary Nodules in Computed Tomography Images', Investigate Radiology, Volume 29, Number 4, pp. 459-465, 1994   DOI
2 Okumura T, Miwa T, Kako j, et al, 'Computer aided diagnosis system for lung cancer based on helical CT images', Proceedings of Medical Imaging by SPIE, Volume 3034, pp. 975-984, 1997   DOI
3 Armato SG HI, Giger ML, Moran CJ, MacMahon H, Blackburn JT, Doi K, 'Computerized Detection of Pulmonary Nodules on CT Scans', RadioGraphic, Volume 19, pp. 1303-1311, 1999
4 Jayaram K. Udupa and Gabor T. Hermen, 3D Imaging in Medicine, p. 3-5, CRC Press, 1991
5 John Bradley, XV : Interactive Image Display for the X Window System, p. 2-65, version 3.10a, 1994
6 Lumisys, Inc., LSDT Software Functions Library Reference Guide, P/N 0066-022, Rev. 10, 1999
7 R.C. Gonzalez, R.E. Woods, Digital Image Processing, p. 458-465, 503-518, Addison-Wesley, 1992
8 NEMA Draft Standards, Digital Imaging and Communications in Medicine (DICOM), Part 1-14
9 D.Y. Kim, J.H. Kim, S.M. Noh, J.W. Park, 'Automated Detection and Volume Calculation of Nodular Lung Cancer on CT Scans', Journal of KISS :Computing Practices, Volume 7, Number 5, pp. 451-457, 2001, 10   과학기술학회마을
10 M.J. Calotto, 'Histogram Analysis Using a Scale-Space Approach', IEEE Transaction on PAMI, pp. 121-129, 1987
11 Scott E. Umbaugh, Computer Vision and Image Processing, p. 197-215, Prentice-Hall, Inc, 1998
12 Dana H. Ballard and Christopher M. Brown, Computer Vision, p. 181-184, Prentice-Hall, Inc, 1982
13 J.R.Parker, Algorithms for Image Processing and Computer Vision, p. 69-108, John-Wiley & Sons, Inc, 1997