313 related articles for article (PubMed ID: 26632059)
1. Detection of masses in digital breast tomosynthesis using complementary information of simulated projection.
Kim ST; Kim DH; Ro YM
Med Phys; 2015 Dec; 42(12):7043-58. PubMed ID: 26632059
[TBL] [Abstract][Full Text] [Related]
2. Computer-aided detection of masses in digital tomosynthesis mammography: comparison of three approaches.
Chan HP; Wei J; Zhang Y; Helvie MA; Moore RH; Sahiner B; Hadjiiski L; Kopans DB
Med Phys; 2008 Sep; 35(9):4087-95. PubMed ID: 18841861
[TBL] [Abstract][Full Text] [Related]
3. Multi-domain features for reducing false positives in automated detection of clustered microcalcifications in digital breast tomosynthesis.
Zhang F; Wu S; Zhang C; Chen Q; Yang X; Jiang K; Zheng J
Med Phys; 2019 Mar; 46(3):1300-1308. PubMed ID: 30661242
[TBL] [Abstract][Full Text] [Related]
4. Characterization of masses in digital breast tomosynthesis: comparison of machine learning in projection views and reconstructed slices.
Chan HP; Wu YT; Sahiner B; Wei J; Helvie MA; Zhang Y; Moore RH; Kopans DB; Hadjiiski L; Way T
Med Phys; 2010 Jul; 37(7):3576-86. PubMed ID: 20831065
[TBL] [Abstract][Full Text] [Related]
5. Developing breast lesion detection algorithms for digital breast tomosynthesis: Leveraging false positive findings.
Hossain MB; Nishikawa RM; Lee J
Med Phys; 2022 Dec; 49(12):7596-7608. PubMed ID: 35916103
[TBL] [Abstract][Full Text] [Related]
6. Multichannel response analysis on 2D projection views for detection of clustered microcalcifications in digital breast tomosynthesis.
Wei J; Chan HP; Hadjiiski LM; Helvie MA; Lu Y; Zhou C; Samala R
Med Phys; 2014 Apr; 41(4):041913. PubMed ID: 24694144
[TBL] [Abstract][Full Text] [Related]
7. Mass detection in reconstructed digital breast tomosynthesis volumes with a computer-aided detection system trained on 2D mammograms.
van Schie G; Wallis MG; Leifland K; Danielsson M; Karssemeijer N
Med Phys; 2013 Apr; 40(4):041902. PubMed ID: 23556896
[TBL] [Abstract][Full Text] [Related]
8. Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography.
Samala RK; Chan HP; Hadjiiski L; Helvie MA; Wei J; Cha K
Med Phys; 2016 Dec; 43(12):6654. PubMed ID: 27908154
[TBL] [Abstract][Full Text] [Related]
9. Computer-aided detection of clustered microcalcifications in digital breast tomosynthesis: a 3D approach.
Sahiner B; Chan HP; Hadjiiski LM; Helvie MA; Wei J; Zhou C; Lu Y
Med Phys; 2012 Jan; 39(1):28-39. PubMed ID: 22225272
[TBL] [Abstract][Full Text] [Related]
10. Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume.
Samala RK; Chan HP; Lu Y; Hadjiiski L; Wei J; Sahiner B; Helvie MA
Med Phys; 2014 Feb; 41(2):021901. PubMed ID: 24506622
[TBL] [Abstract][Full Text] [Related]
11. The simulation of 3D mass models in 2D digital mammography and breast tomosynthesis.
Shaheen E; De Keyzer F; Bosmans H; Dance DR; Young KC; Van Ongeval C
Med Phys; 2014 Aug; 41(8):081913. PubMed ID: 25086544
[TBL] [Abstract][Full Text] [Related]
12. Analysis of computer-aided detection techniques and signal characteristics for clustered microcalcifications on digital mammography and digital breast tomosynthesis.
Samala RK; Chan HP; Hadjiiski LM; Helvie MA
Phys Med Biol; 2016 Oct; 61(19):7092-7112. PubMed ID: 27648708
[TBL] [Abstract][Full Text] [Related]
13. Computer-aided detection of mass in digital breast tomosynthesis using a faster region-based convolutional neural network.
Fan M; Li Y; Zheng S; Peng W; Tang W; Li L
Methods; 2019 Aug; 166():103-111. PubMed ID: 30771490
[TBL] [Abstract][Full Text] [Related]
14. Computerized mass detection for digital breast tomosynthesis directly from the projection images.
Reiser I; Nishikawa RM; Giger ML; Wu T; Rafferty EA; Moore R; Kopans DB
Med Phys; 2006 Feb; 33(2):482-91. PubMed ID: 16532956
[TBL] [Abstract][Full Text] [Related]
15. Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers.
Van de Sompel D; Brady SM; Boone J
Med Image Anal; 2011 Feb; 15(1):53-70. PubMed ID: 20713313
[TBL] [Abstract][Full Text] [Related]
16. Breast mass detection using slice conspicuity in 3D reconstructed digital breast volumes.
Kim ST; Kim DH; Ro YM
Phys Med Biol; 2014 Sep; 59(17):5003-23. PubMed ID: 25119017
[TBL] [Abstract][Full Text] [Related]
17. Evaluation of a variable dose acquisition technique for microcalcification and mass detection in digital breast tomosynthesis.
Das M; Gifford HC; O'Connor JM; Glick SJ
Med Phys; 2009 Jun; 36(6):1976-84. PubMed ID: 19610286
[TBL] [Abstract][Full Text] [Related]
18. A computer simulation study comparing lesion detection accuracy with digital mammography, breast tomosynthesis, and cone-beam CT breast imaging.
Gong X; Glick SJ; Liu B; Vedula AA; Thacker S
Med Phys; 2006 Apr; 33(4):1041-52. PubMed ID: 16696481
[TBL] [Abstract][Full Text] [Related]
19. The simulation of 3D microcalcification clusters in 2D digital mammography and breast tomosynthesis.
Shaheen E; Van Ongeval C; Zanca F; Cockmartin L; Marshall N; Jacobs J; Young KC; R Dance D; Bosmans H
Med Phys; 2011 Dec; 38(12):6659-71. PubMed ID: 22149848
[TBL] [Abstract][Full Text] [Related]
20. Improving mass detection using combined feature representations from projection views and reconstructed volume of DBT and boosting based classification with feature selection.
Kim DH; Kim ST; Ro YM
Phys Med Biol; 2015 Nov; 60(22):8809-32. PubMed ID: 26529080
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
