88 related articles for article (PubMed ID: 23182603)
1. Fast opposite weight learning rules with application in breast cancer diagnosis.
Saki F; Tahmasbi A; Soltanian-Zadeh H; Shokouhi SB
Comput Biol Med; 2013 Jan; 43(1):32-41. PubMed ID: 23182603
[TBL] [Abstract][Full Text] [Related]
2. Classification of benign and malignant masses based on Zernike moments.
Tahmasbi A; Saki F; Shokouhi SB
Comput Biol Med; 2011 Aug; 41(8):726-35. PubMed ID: 21722886
[TBL] [Abstract][Full Text] [Related]
3. Computer-aided characterization of mammographic masses: accuracy of mass segmentation and its effects on characterization.
Sahiner B; Petrick N; Chan HP; Hadjiiski LM; Paramagul C; Helvie MA; Gurcan MN
IEEE Trans Med Imaging; 2001 Dec; 20(12):1275-84. PubMed ID: 11811827
[TBL] [Abstract][Full Text] [Related]
4. Classification of mammographic masses using generalized dynamic fuzzy neural networks.
Lim WK; Er MJ
Med Phys; 2004 May; 31(5):1288-95. PubMed ID: 15191321
[TBL] [Abstract][Full Text] [Related]
5. Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network.
Kooi T; van Ginneken B; Karssemeijer N; den Heeten A
Med Phys; 2017 Mar; 44(3):1017-1027. PubMed ID: 28094850
[TBL] [Abstract][Full Text] [Related]
6. Characterization of mammographic masses using a gradient-based segmentation algorithm and a neural classifier.
Delogu P; Evelina Fantacci M; Kasae P; Retico A
Comput Biol Med; 2007 Oct; 37(10):1479-91. PubMed ID: 17383623
[TBL] [Abstract][Full Text] [Related]
7. 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
[TBL] [Abstract][Full Text] [Related]
8. Retrieval boosted computer-aided diagnosis of clustered microcalcifications for breast cancer.
Jing H; Yang Y; Nishikawa RM
Med Phys; 2012 Feb; 39(2):676-85. PubMed ID: 22320777
[TBL] [Abstract][Full Text] [Related]
9. Improving the Mann-Whitney statistical test for feature selection: an approach in breast cancer diagnosis on mammography.
Pérez NP; Guevara López MA; Silva A; Ramos I
Artif Intell Med; 2015 Jan; 63(1):19-31. PubMed ID: 25555756
[TBL] [Abstract][Full Text] [Related]
10. A model-based framework for the detection of spiculated masses on mammography.
Sampat MP; Bovik AC; Whitman GJ; Markey MK
Med Phys; 2008 May; 35(5):2110-23. PubMed ID: 18561687
[TBL] [Abstract][Full Text] [Related]
11. Influence of using manual or automatic breast density information in a mass detection CAD system.
Oliver A; Lladó X; Freixenet J; Martí R; Pérez E; Pont J; Zwiggelaar R
Acad Radiol; 2010 Jul; 17(7):877-83. PubMed ID: 20540910
[TBL] [Abstract][Full Text] [Related]
12. Geometry-Based Pectoral Muscle Segmentation From MLO Mammogram Views.
Taghanaki SA; Liu Y; Miles B; Hamarneh G
IEEE Trans Biomed Eng; 2017 Nov; 64(11):2662-2671. PubMed ID: 28129144
[TBL] [Abstract][Full Text] [Related]
13. A CADx scheme for mammography empowered with topological information from clustered microcalcifications' atlases.
Andreadis II; Spyrou GM; Nikita KS
IEEE J Biomed Health Inform; 2015 Jan; 19(1):166-73. PubMed ID: 25073178
[TBL] [Abstract][Full Text] [Related]
14. Eigendetection of masses considering false positive reduction and breast density information.
Freixenet J; Oliver A; Martí R; Lladó X; Pont J; Pérez E; Denton ER; Zwiggelaar R
Med Phys; 2008 May; 35(5):1840-53. PubMed ID: 18561659
[TBL] [Abstract][Full Text] [Related]
15. Linear and neural models for classifying breast masses.
Fogel DB; Wasson EC; Boughton EM; Porto VW; Angeline PJ
IEEE Trans Med Imaging; 1998 Jun; 17(3):485-8. PubMed ID: 9735913
[TBL] [Abstract][Full Text] [Related]
16. Computerized-aid diagnosis of breast mass using ultrasound image.
Tian JW; Sun LT; Guo YH; Cheng HD; Zhang YT
Med Phys; 2007 Aug; 34(8):3158-64. PubMed ID: 17879777
[TBL] [Abstract][Full Text] [Related]
17. Assessment and Classification of Mass Lesions Based on Expert Knowledge Using Mammographic Analysis.
Arzehgar A; Khalilzadeh MM; Varshoei F
Curr Med Imaging Rev; 2019; 15(2):199-208. PubMed ID: 31975666
[TBL] [Abstract][Full Text] [Related]
18. Use of border information in the classification of mammographic masses.
Varela C; Timp S; Karssemeijer N
Phys Med Biol; 2006 Jan; 51(2):425-41. PubMed ID: 16394348
[TBL] [Abstract][Full Text] [Related]
19. A retrieval-based computer-aided diagnosis system for the characterization of liver lesions in CT scans.
Dankerl P; Cavallaro A; Tsymbal A; Costa MJ; Suehling M; Janka R; Uder M; Hammon M
Acad Radiol; 2013 Dec; 20(12):1526-34. PubMed ID: 24200479
[TBL] [Abstract][Full Text] [Related]
20. Temporal change analysis for characterization of mass lesions in mammography.
Timp S; Varela C; Karssemeijer N
IEEE Trans Med Imaging; 2007 Jul; 26(7):945-53. PubMed ID: 17649908
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
