Open Access Open Access  Restricted Access Subscription or Fee Access

Textural Analysis for the Accuracy in Diagnosis of Medical Scan/CT Images

M. Vanitha, R. Balasubramanian

Abstract


To determine the accuracy of normal tissue scan images from the abnormal cases, the GLCM (Grey-Level Co-occurrence matrix) and their derived parameters such as homogeneity of the images and energy level calculations were approached. These structural and textural parameters were calculated by using mathematical formulae. In each case 20 abdominal scan images of both normal and abnormal patients were employed. The data generated out of this present investigation was tabulated and statistically analyzed. The analysis for energy level on the images disclosed that there was a clear distinguish between normal tissue and abnormal tissue. The above results are discussed with relation to the accuracy.

Keywords


Textural Features of CT Images; Statistical Design For Image Studies; Medical Image Textural Analysis.

Full Text:

PDF

References


P.Taylor,Champness.J, R. Given-Wilson. Johnston. K, H.Potts. Impact of computer-aided detection prompts on the sensitivity and specificity of screening mammography.Health technology Assessment 9(6),2005. p.1-70.

Q.Ji.,J.Engel, E.Craine.Texture analysis for classification of cervix lesions. Medical Imaging, IEEE Transactions on Vol. No.19. issue 11. 2000. Pp.1144-1149.

R.Haralick. Statistical and structural approaches to texture. Proceeedings of IEEE, 67. 1979. pp. 786-804.

C. Rafael, Gonzalez, Woods, E. Richard. Digital image processing. Prentice Hall. NJ. 2002.

Y.Wang, Itoh. K, Taniguchi. N, Toei, H, Kawai. F, Nakamura. M, Omoto. K, Yokoto. K, Ono. T. Studies on tissue characterization by texture analysis with co-occurrence matrix method using ultra sonography and CT imagine, Journal of Medical Ultrasonics,29 Issue4, 2002,p.211-223.

J.C.Felipe, Traina, A.J.M, Traina, C. Jr. Retrieval by content of medical images using texture for tissue identification. Computer Based Medical Systems,Proceedings of !6th IEEE Symposium 26- 27, 2003, p.175-180.

M.A. Sheppard, Liwen Shih. P6C-2 Image Texture Clustering for prostate Ultra Diagnosis, Ultrasonics Symposium,2007, IEEE 28-31, 2007. P.2473-2476.

C.C.Venters , Cooper, M. Content based image retrieval, Technology Report: JTAP-054, JISC Technology Application Program: 2000.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.