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Journal Abstract Search
102 related items for PubMed ID: 9157269
1. Using tissue texture surrounding calcification clusters to predict benign vs malignant outcomes. Thiele DL, Kimme-Smith C, Johnson TD, McCombs M, Bassett LW. Med Phys; 1996 Apr; 23(4):549-55. PubMed ID: 9157269 [Abstract] [Full Text] [Related]
2. Computerized analysis of mammographic microcalcifications in morphological and texture feature spaces. Chan HP, Sahiner B, Lam KL, Petrick N, Helvie MA, Goodsitt MM, Adler DD. Med Phys; 1998 Oct; 25(10):2007-19. PubMed ID: 9800710 [Abstract] [Full Text] [Related]
3. Computerized classification of malignant and benign microcalcifications on mammograms: texture analysis using an artificial neural network. Chan HP, Sahiner B, Petrick N, Helvie MA, Lam KL, Adler DD, Goodsitt MM. Phys Med Biol; 1997 Mar; 42(3):549-67. PubMed ID: 9080535 [Abstract] [Full Text] [Related]
6. Detection of breast masses in mammograms by density slicing and texture flow-field analysis. Mudigonda NR, Rangayyan RM, Desautels JE. IEEE Trans Med Imaging; 2001 Dec; 20(12):1215-27. PubMed ID: 11811822 [Abstract] [Full Text] [Related]
9. Wavelet-based 3D reconstruction of microcalcification clusters from two mammographic views: new evidence that fractal tumors are malignant and Euclidean tumors are benign. Batchelder KA, Tanenbaum AB, Albert S, Guimond L, Kestener P, Arneodo A, Khalil A. PLoS One; 2014 Dec; 9(9):e107580. PubMed ID: 25222610 [Abstract] [Full Text] [Related]
10. Segmentation of suspicious clustered microcalcifications in mammograms. Gavrielides MA, Lo JY, Vargas-Voracek R, Floyd CE. Med Phys; 2000 Jan; 27(1):13-22. PubMed ID: 10659733 [Abstract] [Full Text] [Related]
13. Computer-aided classification of mammographic masses and normal tissue: linear discriminant analysis in texture feature space. Chan HP, Wei D, Helvie MA, Sahiner B, Adler DD, Goodsitt MM, Petrick N. Phys Med Biol; 1995 May; 40(5):857-76. PubMed ID: 7652012 [Abstract] [Full Text] [Related]
14. Analysis of clustered microcalcifications by using a single numeric classifier extracted from mammographic digital images. Buchbinder SS, Leichter IS, Bamberger PN, Novak B, Lederman R, Fields S, Behar DJ. Acad Radiol; 1998 Nov; 5(11):779-84. PubMed ID: 9809076 [Abstract] [Full Text] [Related]
15. A simulation model of clustered breast microcalcifications. Lefebvre F, Benali H, Gilles R, Di Paola R. Med Phys; 1994 Dec; 21(12):1865-74. PubMed ID: 7700193 [Abstract] [Full Text] [Related]
16. Automated analysis of mammographic densities. Byng JW, Boyd NF, Fishell E, Jong RA, Yaffe MJ. Phys Med Biol; 1996 May; 41(5):909-23. PubMed ID: 8735257 [Abstract] [Full Text] [Related]
18. Computerized evaluation of mammographic lesions: what diagnostic role does the shape of the individual microcalcifications play compared with the geometry of the cluster? Leichter I, Lederman R, Buchbinder SS, Bamberger P, Novak B, Fields S. AJR Am J Roentgenol; 2004 Mar; 182(3):705-12. PubMed ID: 14975973 [Abstract] [Full Text] [Related]
19. An improved shift-invariant artificial neural network for computerized detection of clustered microcalcifications in digital mammograms. Zhang W, Doi K, Giger ML, Nishikawa RM, Schmidt RA. Med Phys; 1996 Apr; 23(4):595-601. PubMed ID: 8860907 [Abstract] [Full Text] [Related]