441 related articles for article (PubMed ID: 31622238)
21. Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.
Al-Masni MA; Al-Antari MA; Park JM; Gi G; Kim TY; Rivera P; Valarezo E; Choi MT; Han SM; Kim TS
Comput Methods Programs Biomed; 2018 Apr; 157():85-94. PubMed ID: 29477437
[TBL] [Abstract][Full Text] [Related]
22. Breast Cancer Classification in Automated Breast Ultrasound Using Multiview Convolutional Neural Network with Transfer Learning.
Wang Y; Choi EJ; Choi Y; Zhang H; Jin GY; Ko SB
Ultrasound Med Biol; 2020 May; 46(5):1119-1132. PubMed ID: 32059918
[TBL] [Abstract][Full Text] [Related]
23. Latent feature representation with depth directional long-term recurrent learning for breast masses in digital breast tomosynthesis.
Kim DH; Kim ST; Chang JM; Ro YM
Phys Med Biol; 2017 Feb; 62(3):1009-1031. PubMed ID: 28081006
[TBL] [Abstract][Full Text] [Related]
24. Transformer-based Deep Neural Network for Breast Cancer Classification on Digital Breast Tomosynthesis Images.
Lee W; Lee H; Lee H; Park EK; Nam H; Kooi T
Radiol Artif Intell; 2023 May; 5(3):e220159. PubMed ID: 37293346
[TBL] [Abstract][Full Text] [Related]
25. Enhancing deep convolutional neural network scheme for breast cancer diagnosis with unlabeled data.
Sun W; Tseng TB; Zhang J; Qian W
Comput Med Imaging Graph; 2017 Apr; 57():4-9. PubMed ID: 27475279
[TBL] [Abstract][Full Text] [Related]
26. Deep Convolutional Neural Network With Adversarial Training for Denoising Digital Breast Tomosynthesis Images.
Gao M; Fessler JA; Chan HP
IEEE Trans Med Imaging; 2021 Jul; 40(7):1805-1816. PubMed ID: 33729933
[TBL] [Abstract][Full Text] [Related]
27. Representation learning for mammography mass lesion classification with convolutional neural networks.
Arevalo J; González FA; Ramos-Pollán R; Oliveira JL; Guevara Lopez MA
Comput Methods Programs Biomed; 2016 Apr; 127():248-57. PubMed ID: 26826901
[TBL] [Abstract][Full Text] [Related]
28. AutoTune: Automatically Tuning Convolutional Neural Networks for Improved Transfer Learning.
Basha SHS; Vinakota SK; Pulabaigari V; Mukherjee S; Dubey SR
Neural Netw; 2021 Jan; 133():112-122. PubMed ID: 33181405
[TBL] [Abstract][Full Text] [Related]
29. Deep Learning in Mammography: Diagnostic Accuracy of a Multipurpose Image Analysis Software in the Detection of Breast Cancer.
Becker AS; Marcon M; Ghafoor S; Wurnig MC; Frauenfelder T; Boss A
Invest Radiol; 2017 Jul; 52(7):434-440. PubMed ID: 28212138
[TBL] [Abstract][Full Text] [Related]
30. Risks of feature leakage and sample size dependencies in deep feature extraction for breast mass classification.
Samala RK; Chan HP; Hadjiiski L; Helvie MA
Med Phys; 2021 Jun; 48(6):2827-2837. PubMed ID: 33368376
[TBL] [Abstract][Full Text] [Related]
31. Characterization of Breast Masses in Digital Breast Tomosynthesis and Digital Mammograms: An Observer Performance Study.
Chan HP; Helvie MA; Hadjiiski L; Jeffries DO; Klein KA; Neal CH; Noroozian M; Paramagul C; Roubidoux MA
Acad Radiol; 2017 Nov; 24(11):1372-1379. PubMed ID: 28647388
[TBL] [Abstract][Full Text] [Related]
32. A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology.
Qiu Y; Yan S; Gundreddy RR; Wang Y; Cheng S; Liu H; Zheng B
J Xray Sci Technol; 2017; 25(5):751-763. PubMed ID: 28436410
[TBL] [Abstract][Full Text] [Related]
33. Improving breast mass classification by shared data with domain transformation using a generative adversarial network.
Muramatsu C; Nishio M; Goto T; Oiwa M; Morita T; Yakami M; Kubo T; Togashi K; Fujita H
Comput Biol Med; 2020 Apr; 119():103698. PubMed ID: 32339129
[TBL] [Abstract][Full Text] [Related]
34. Local Tumor Staging of Breast Cancer: Digital Mammography versus Digital Mammography Plus Tomosynthesis.
Fontaine M; Tourasse C; Pages E; Laurent N; Laffargue G; Millet I; Molinari N; Taourel P
Radiology; 2019 Jun; 291(3):594-603. PubMed ID: 30964425
[TBL] [Abstract][Full Text] [Related]
35. Transfer learning using a multi-scale and multi-network ensemble for skin lesion classification.
Mahbod A; Schaefer G; Wang C; Dorffner G; Ecker R; Ellinger I
Comput Methods Programs Biomed; 2020 Sep; 193():105475. PubMed ID: 32268255
[TBL] [Abstract][Full Text] [Related]
36. A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification.
Al-Antari MA; Al-Masni MA; Choi MT; Han SM; Kim TS
Int J Med Inform; 2018 Sep; 117():44-54. PubMed ID: 30032964
[TBL] [Abstract][Full Text] [Related]
37. Deep learning networks find unique mammographic differences in previous negative mammograms between interval and screen-detected cancers: a case-case study.
Hinton B; Ma L; Mahmoudzadeh AP; Malkov S; Fan B; Greenwood H; Joe B; Lee V; Kerlikowske K; Shepherd J
Cancer Imaging; 2019 Jun; 19(1):41. PubMed ID: 31228956
[TBL] [Abstract][Full Text] [Related]
38. One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection: do we need more?
Rodriguez-Ruiz A; Gubern-Merida A; Imhof-Tas M; Lardenoije S; Wanders AJT; Andersson I; Zackrisson S; Lång K; Dustler M; Karssemeijer N; Mann RM; Sechopoulos I
Eur Radiol; 2018 May; 28(5):1938-1948. PubMed ID: 29230524
[TBL] [Abstract][Full Text] [Related]
39. Avoiding Tissue Overlap in 2D Images: Single-Slice DBT Classification Using Convolutional Neural Networks.
Mendes J; Matela N; Garcia N
Tomography; 2023 Feb; 9(1):398-412. PubMed ID: 36828384
[TBL] [Abstract][Full Text] [Related]
40. SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis.
Gao F; Wu T; Li J; Zheng B; Ruan L; Shang D; Patel B
Comput Med Imaging Graph; 2018 Dec; 70():53-62. PubMed ID: 30292910
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
