Intensity independent texture analysis in screening mammograms

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7361 LNCS, Issue , 2012, Pages 474-481

  Li, Xi Zhao ^a   Williams, Simon ^a   Bottema, Murk J ^a  

^a FLINDERS UNIVERSITY   (Australia)

Author keywords

breast cancer; computer aided mammography; mass detection; texture

Indexed keywords

BREAST CANCER; COMPUTER-AIDED MAMMOGRAPHIES; INTENSITY-BASED; LINEAR STRUCTURES; LOCAL MEAN; LOCAL STANDARD DEVIATION; MALIGNANT MASS; MASS DETECTION; NORMALIZED IMAGE; SCREENING MAMMOGRAM; STANDARD DEVIATION; TEXTURE ANALYSIS; TEXTURE FEATURES; TEXTURE INFORMATION;

DISEASES; MAMMOGRAPHY; MEDICAL IMAGING; TEXTURES; X RAY SCREENS;

IMAGE TEXTURE;

EID: 84864863833     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-31271-7_61     Document Type: Conference Paper

References (14)

1. Grim J., Somol P., Haindl M., Daneš J.: Computer-Aided evaluation of screening mammograms based on local texture models. IEEE Transaction on Image Processing. 18(4), 765-773 (2009).
2. Gupta, R., Undrill, P.E.: The use of texture analysis to delineate suspicious masses in mammography. Phys. Med. Biol. 40, 835-855 (1995
3. Karssemeijer, N.: Automated classification of parenchymal patterns in mammograms. Physics and Medicine in Biology 43, 365-378 (1998
4. Karssemeijer, N., te Brake, G.M., et al.: Detection of stellate distortions in mammograms. IEEE Transactions on Medical Imaging 15(5), 611-619 (1996
5. Malik, J., Belongie, S., Shi, J., Leung, T.: Textons, contours and regions; Cue integration in image segmentation. In: IEEE Int. Conf. on Comp. Vision, Corfu, Greece. IEEE (1999
6. McCormack, V.A., dos Santos Silva, I.: Breast density and parenchymal patterns as markers of breast cancer risk: A meta-Analysis. Cancer Epidemiology, Biomarkers and Prevention 15(6), 1159-1169 (2006
7. Mudigonda, N.R., Rangayyan, R.M., Desautels, J.E.L.: Detection of breast masses in mammograms by density slicing and texture flow-field analysis. IEEE Transactions on Medical Imaging 20(12), 1215-1227 (2001
8. Palma, G., Bloch, I., Muller, S.: Spiculated Lesions and Architectural Distortions Detection in Digital Breast Tomosynthesis Datasets. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds.) IWDM 2010. LNCS, vol. 6136, pp. 712-719. Springer, Heidelberg (2010
9. Sahiner, B., Chan, H.-P., Petrick, N., Halvie, M.A., Goodsitt, M.M.: Computerized characterization of masses on mammograms: The rubber band straightening transform and texture analysis. Medical Physics 25(4), 516-526 (1998
10. Sahiner, B., Chan, H.-P., Petrick, N., Helvie, M.A., Hadjiiski, L.M.: Improvement of mammographic mass characterization using spiculation measures and morphological features. Medical Physics 28(7), 1455-1465 (2001
11. Tourassi, G.D., Delong, D.M., Floyd Jr., C.E.: A study on the computerized fractal analysis of architectural distortions in screening mammograms. Phys. Med. Biol. 51, 1299-1312 (2006
12. Wessel, C., Schnabel, J.A., Brady, S.M.: Towards More Realistic Biomechanical Modelling of Tumours under Mammographic Compressions. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds.) IWDM 2010. LNCS, vol. 6136, pp. 481-489. Springer, Heidelberg (2010
13. Wolfe, J.N.: Risk for breast cancer development determined by mammographic parenchymal pattern. Cancer 37(5), 2486-2492 (1976
14. Zwiggelaar, R.: Local Greylevel Appearance Histogram Based Texture Segmentation. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds.) IWDM 2010. LNCS, vol. 6136, pp. 175-182. Springer, Heidelberg (2010)