768 related articles for article (PubMed ID: 28391823)
1. 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]
2. 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]
3. Review of recent advances in segmentation of the breast boundary and the pectoral muscle in mammograms.
Mustra M; Grgic M; Rangayyan RM
Med Biol Eng Comput; 2016 Jul; 54(7):1003-24. PubMed ID: 26546074
[TBL] [Abstract][Full Text] [Related]
4. Automatic Pectoral Muscle Region Segmentation in Mammograms Using Genetic Algorithm and Morphological Selection.
Shen R; Yan K; Xiao F; Chang J; Jiang C; Zhou K
J Digit Imaging; 2018 Oct; 31(5):680-691. PubMed ID: 29582242
[TBL] [Abstract][Full Text] [Related]
5. A Method for Microcalcifications Detection in Breast Mammograms.
Alasadi AH; Al-Saedi AK
J Med Syst; 2017 Apr; 41(4):68. PubMed ID: 28284000
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Segmentation for the enhancement of microcalcifications in digital mammograms.
Milosevic M; Jankovic D; Peulic A
Technol Health Care; 2014; 22(5):701-15. PubMed ID: 25059254
[TBL] [Abstract][Full Text] [Related]
8. Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks.
Bandeira Diniz JO; Bandeira Diniz PH; Azevedo Valente TL; Corrêa Silva A; de Paiva AC; Gattass M
Comput Methods Programs Biomed; 2018 Mar; 156():191-207. PubMed ID: 29428071
[TBL] [Abstract][Full Text] [Related]
9. Detection and Segmentation of Pectoral Muscle on MLO-View Mammogram Using Enhancement Filter.
Vikhe PS; Thool VR
J Med Syst; 2017 Oct; 41(12):190. PubMed ID: 29071592
[TBL] [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
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. A hierarchical pipeline for breast boundary segmentation and calcification detection in mammograms.
Shi P; Zhong J; Rampun A; Wang H
Comput Biol Med; 2018 May; 96():178-188. PubMed ID: 29597143
[TBL] [Abstract][Full Text] [Related]
13. Automatic pectoral muscle segmentation on mediolateral oblique view mammograms.
Kwok SM; Chandrasekhar R; Attikiouzel Y; Rickard MT
IEEE Trans Med Imaging; 2004 Sep; 23(9):1129-40. PubMed ID: 15377122
[TBL] [Abstract][Full Text] [Related]
14. Automatic Detection of Pectoral Muscle Region for Computer-Aided Diagnosis Using MIAS Mammograms.
Yoon WB; Oh JE; Chae EY; Kim HH; Lee SY; Kim KG
Biomed Res Int; 2016; 2016():5967580. PubMed ID: 27847817
[TBL] [Abstract][Full Text] [Related]
15. A novel automatic suspicious mass regions identification using Havrda & Charvat entropy and Otsu's N thresholding.
Kurt B; Nabiyev VV; Turhan K
Comput Methods Programs Biomed; 2014 May; 114(3):349-60. PubMed ID: 24681199
[TBL] [Abstract][Full Text] [Related]
16. Computer aided detection of clusters of microcalcifications on full field digital mammograms.
Ge J; Sahiner B; Hadjiiski LM; Chan HP; Wei J; Helvie MA; Zhou C
Med Phys; 2006 Aug; 33(8):2975-88. PubMed ID: 16964876
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Automatic identification of the pectoral muscle in mammograms.
Ferrari RJ; Rangayyan RM; Desautels JE; Borges RA; Frère AF
IEEE Trans Med Imaging; 2004 Feb; 23(2):232-45. PubMed ID: 14964567
[TBL] [Abstract][Full Text] [Related]
19. Computer-aided identification of the pectoral muscle in digitized mammograms.
Camilus KS; Govindan VK; Sathidevi PS
J Digit Imaging; 2010 Oct; 23(5):562-80. PubMed ID: 19816741
[TBL] [Abstract][Full Text] [Related]
20. A New Breast Border Extraction and Contrast Enhancement Technique with Digital Mammogram Images for Improved Detection of Breast Cancer.
Hazarika M; Mahanta LB
Asian Pac J Cancer Prev; 2018 Aug; 19(8):2141-2148. PubMed ID: 30139217
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]