337 related articles for article (PubMed ID: 29210358)
1. Computer-aided assessment of breast density: comparison of supervised deep learning and feature-based statistical learning.
Li S; Wei J; Chan HP; Helvie MA; Roubidoux MA; Lu Y; Zhou C; Hadjiiski LM; Samala RK
Phys Med Biol; 2018 Jan; 63(2):025005. PubMed ID: 29210358
[TBL] [Abstract][Full Text] [Related]
2. Automated pectoral muscle identification on MLO-view mammograms: Comparison of deep neural network to conventional computer vision.
Ma X; Wei J; Zhou C; Helvie MA; Chan HP; Hadjiiski LM; Lu Y
Med Phys; 2019 May; 46(5):2103-2114. PubMed ID: 30771257
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification.
Li X; Qin G; He Q; Sun L; Zeng H; He Z; Chen W; Zhen X; Zhou L
Eur Radiol; 2020 Feb; 30(2):778-788. PubMed ID: 31691121
[TBL] [Abstract][Full Text] [Related]
5. Multi-task transfer learning deep convolutional neural network: application to computer-aided diagnosis of breast cancer on mammograms.
Samala RK; Chan HP; Hadjiiski LM; Helvie MA; Cha KH; Richter CD
Phys Med Biol; 2017 Nov; 62(23):8894-8908. PubMed ID: 29035873
[TBL] [Abstract][Full Text] [Related]
6. Mammographic Breast Density Assessment Using Deep Learning: Clinical Implementation.
Lehman CD; Yala A; Schuster T; Dontchos B; Bahl M; Swanson K; Barzilay R
Radiology; 2019 Jan; 290(1):52-58. PubMed ID: 30325282
[TBL] [Abstract][Full Text] [Related]
7. Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks.
Yi PH; Lin A; Wei J; Yu AC; Sair HI; Hui FK; Hager GD; Harvey SC
J Digit Imaging; 2019 Aug; 32(4):565-570. PubMed ID: 31197559
[TBL] [Abstract][Full Text] [Related]
8. Mammographic density measured with quantitative computer-aided method: comparison with radiologists' estimates and BI-RADS categories.
Martin KE; Helvie MA; Zhou C; Roubidoux MA; Bailey JE; Paramagul C; Blane CE; Klein KA; Sonnad SS; Chan HP
Radiology; 2006 Sep; 240(3):656-65. PubMed ID: 16857974
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Comparison of a Deep Learning Risk Score and Standard Mammographic Density Score for Breast Cancer Risk Prediction.
Dembrower K; Liu Y; Azizpour H; Eklund M; Smith K; Lindholm P; Strand F
Radiology; 2020 Feb; 294(2):265-272. PubMed ID: 31845842
[TBL] [Abstract][Full Text] [Related]
11. Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm.
Heidari M; Khuzani AZ; Hollingsworth AB; Danala G; Mirniaharikandehei S; Qiu Y; Liu H; Zheng B
Phys Med Biol; 2018 Jan; 63(3):035020. PubMed ID: 29239858
[TBL] [Abstract][Full Text] [Related]
12. Mass detection in digital breast tomosynthesis data using convolutional neural networks and multiple instance learning.
Yousefi M; Krzyżak A; Suen CY
Comput Biol Med; 2018 May; 96():283-293. PubMed ID: 29665537
[TBL] [Abstract][Full Text] [Related]
13. A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction.
Yala A; Lehman C; Schuster T; Portnoi T; Barzilay R
Radiology; 2019 Jul; 292(1):60-66. PubMed ID: 31063083
[TBL] [Abstract][Full Text] [Related]
14. Determination of mammographic breast density using a deep convolutional neural network.
Ciritsis A; Rossi C; Vittoria De Martini I; Eberhard M; Marcon M; Becker AS; Berger N; Boss A
Br J Radiol; 2019 Jan; 92(1093):20180691. PubMed ID: 30209957
[TBL] [Abstract][Full Text] [Related]
15. Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms.
Akselrod-Ballin A; Chorev M; Shoshan Y; Spiro A; Hazan A; Melamed R; Barkan E; Herzel E; Naor S; Karavani E; Koren G; Goldschmidt Y; Shalev V; Rosen-Zvi M; Guindy M
Radiology; 2019 Aug; 292(2):331-342. PubMed ID: 31210611
[TBL] [Abstract][Full Text] [Related]
16. Global parenchymal texture features based on histograms of oriented gradients improve cancer development risk estimation from healthy breasts.
Pérez-Benito FJ; Signol F; Pérez-Cortés JC; Pollán M; Pérez-Gómez B; Salas-Trejo D; Casals M; Martínez I; LLobet R
Comput Methods Programs Biomed; 2019 Aug; 177():123-132. PubMed ID: 31319940
[TBL] [Abstract][Full Text] [Related]
17. Parenchymal texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment.
Zheng Y; Keller BM; Ray S; Wang Y; Conant EF; Gee JC; Kontos D
Med Phys; 2015 Jul; 42(7):4149-60. PubMed ID: 26133615
[TBL] [Abstract][Full Text] [Related]
18. A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studies.
Wang C; Brentnall AR; Cuzick J; Harkness EF; Evans DG; Astley S
Breast Cancer Res; 2017 Oct; 19(1):114. PubMed ID: 29047382
[TBL] [Abstract][Full Text] [Related]
19. Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction.
Gastounioti A; Kasi CD; Scott CG; Brandt KR; Jensen MR; Hruska CB; Wu FF; Norman AD; Conant EF; Winham SJ; Kerlikowske K; Kontos D; Vachon CM
Radiology; 2020 Jul; 296(1):24-31. PubMed ID: 32396041
[TBL] [Abstract][Full Text] [Related]
20. A deep learning system to obtain the optimal parameters for a threshold-based breast and dense tissue segmentation.
Pérez-Benito FJ; Signol F; Perez-Cortes JC; Fuster-Baggetto A; Pollan M; Pérez-Gómez B; Salas-Trejo D; Casals M; Martínez I; LLobet R
Comput Methods Programs Biomed; 2020 Oct; 195():105668. PubMed ID: 32755754
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
