230 related articles for article (PubMed ID: 28582921)
1. Grouped fuzzy SVM with EM-based partition of sample space for clustered microcalcification detection.
Wang H; Feng J; Wang H
Technol Health Care; 2017 Jul; 25(S1):325-336. PubMed ID: 28582921
[TBL] [Abstract][Full Text] [Related]
2. A support vector machine approach for detection of microcalcifications.
El-Naqa I; Yang Y; Wernick MN; Galatsanos NP; Nishikawa RM
IEEE Trans Med Imaging; 2002 Dec; 21(12):1552-63. PubMed ID: 12588039
[TBL] [Abstract][Full Text] [Related]
3. Radiomics based detection and characterization of suspicious lesions on full field digital mammograms.
Sapate SG; Mahajan A; Talbar SN; Sable N; Desai S; Thakur M
Comput Methods Programs Biomed; 2018 Sep; 163():1-20. PubMed ID: 30119844
[TBL] [Abstract][Full Text] [Related]
4. Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.
Zyout I; Czajkowska J; Grzegorzek M
Comput Med Imaging Graph; 2015 Dec; 46 Pt 2():95-107. PubMed ID: 25795630
[TBL] [Abstract][Full Text] [Related]
5. False Positive Reduction by an Annular Model as a Set of Few Features for Microcalcification Detection to Assist Early Diagnosis of Breast Cancer.
Hernández-Capistrán J; Martínez-Carballido JF; Rosas-Romero R
J Med Syst; 2018 Jun; 42(8):134. PubMed ID: 29915992
[TBL] [Abstract][Full Text] [Related]
6. An Efficient Segmentation and Classification System in Medical Images Using Intuitionist Possibilistic Fuzzy C-Mean Clustering and Fuzzy SVM Algorithm.
Chowdhary CL; Mittal M; P K; Pattanaik PA; Marszalek Z
Sensors (Basel); 2020 Jul; 20(14):. PubMed ID: 32668793
[TBL] [Abstract][Full Text] [Related]
7. Relevance vector machine for automatic detection of clustered microcalcifications.
Wei L; Yang Y; Nishikawa RM; Wernick MN; Edwards A
IEEE Trans Med Imaging; 2005 Oct; 24(10):1278-85. PubMed ID: 16229415
[TBL] [Abstract][Full Text] [Related]
8. Location of mammograms ROI's and reduction of false-positive.
Salazar-Licea LA; Pedraza-Ortega JC; Pastrana-Palma A; Aceves-Fernandez MA
Comput Methods Programs Biomed; 2017 May; 143():97-111. PubMed ID: 28391823
[TBL] [Abstract][Full Text] [Related]
9. Mass type-specific sparse representation for mass classification in computer-aided detection on mammograms.
Kim DH; Lee SH; Ro YM
Biomed Eng Online; 2013; 12 Suppl 1(Suppl 1):S3. PubMed ID: 24564973
[TBL] [Abstract][Full Text] [Related]
10. Microcalcification detection based on wavelet domain hidden markov tree model: study for inclusion to computer aided diagnostic prompting system.
Regentova E; Zhang L; Zheng J; Veni G
Med Phys; 2007 Jun; 34(6):2206-19. PubMed ID: 17654922
[TBL] [Abstract][Full Text] [Related]
11. Improving the accuracy in detection of clustered microcalcifications with a context-sensitive classification model.
Wang J; Nishikawa RM; Yang Y
Med Phys; 2016 Jan; 43(1):159. PubMed ID: 26745908
[TBL] [Abstract][Full Text] [Related]
12. Classification of breast regions as mass and non-mass based on digital mammograms using taxonomic indexes and SVM.
Soares Sérvulo de Oliveira F; Oseas de Carvalho Filho A; Corrêa Silva A; Cardoso de Paiva A; Gattass M
Comput Biol Med; 2015 Feb; 57():42-53. PubMed ID: 25528696
[TBL] [Abstract][Full Text] [Related]
13. A new approach for clustered MCs classification with sparse features learning and TWSVM.
Zhang XS
ScientificWorldJournal; 2014; 2014():970287. PubMed ID: 24764773
[TBL] [Abstract][Full Text] [Related]
14. Automatic detection of microcalcifications using mathematical morphology and a support vector machine.
Zhang E; Wang F; Li Y; Bai X
Biomed Mater Eng; 2014; 24(1):53-9. PubMed ID: 24211882
[TBL] [Abstract][Full Text] [Related]
15. 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
[TBL] [Abstract][Full Text] [Related]
16. Multi-View Probabilistic Classification of Breast Microcalcifications.
Bekker AJ; Shalhon M; Greenspan H; Goldberger J
IEEE Trans Med Imaging; 2016 Feb; 35(2):645-53. PubMed ID: 26452277
[TBL] [Abstract][Full Text] [Related]
17. Classification of Benign and Malignant Breast Masses on Mammograms for Large Datasets using Core Vector Machines.
Jebamony J; Jacob D
Curr Med Imaging; 2020; 16(6):703-710. PubMed ID: 32723242
[TBL] [Abstract][Full Text] [Related]
18. A novel approach to microcalcification detection using fuzzy logic technique.
Cheng HD; Lui YM; Freimanis RI
IEEE Trans Med Imaging; 1998 Jun; 17(3):442-50. PubMed ID: 9735907
[TBL] [Abstract][Full Text] [Related]
19. Computer Aided Detection of Clustered Microcalcification: A Survey.
Kumar MNA; Kumar MNA; Sheshadri HS
Curr Med Imaging Rev; 2019; 15(2):132-149. PubMed ID: 31975660
[TBL] [Abstract][Full Text] [Related]
20. Breast microcalcifications detection based on fusing features with DTCWT.
Wang Z; Xin J; Zhang Q; Gao S; Ma C; Ren J; Zhang H; Qian W; Zhu W; Zhang X; Liu J
J Xray Sci Technol; 2020; 28(2):197-218. PubMed ID: 31985483
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
