339 related articles for article (PubMed ID: 35085352)
1. Breast lesions classifications of mammographic images using a deep convolutional neural network-based approach.
Mahmood T; Li J; Pei Y; Akhtar F; Rehman MU; Wasti SH
PLoS One; 2022; 17(1):e0263126. PubMed ID: 35085352
[TBL] [Abstract][Full Text] [Related]
2. Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN).
Agnes SA; Anitha J; Pandian SIA; Peter JD
J Med Syst; 2019 Dec; 44(1):30. PubMed ID: 31838610
[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. An Automated In-Depth Feature Learning Algorithm for Breast Abnormality Prognosis and Robust Characterization from Mammography Images Using Deep Transfer Learning.
Mahmood T; Li J; Pei Y; Akhtar F
Biology (Basel); 2021 Sep; 10(9):. PubMed ID: 34571736
[TBL] [Abstract][Full Text] [Related]
5. Deep convolutional neural networks for mammography: advances, challenges and applications.
Abdelhafiz D; Yang C; Ammar R; Nabavi S
BMC Bioinformatics; 2019 Jun; 20(Suppl 11):281. PubMed ID: 31167642
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. DV-DCNN: Dual-view deep convolutional neural network for matching detected masses in mammograms.
AlGhamdi M; Abdel-Mottaleb M
Comput Methods Programs Biomed; 2021 Aug; 207():106152. PubMed ID: 34058629
[TBL] [Abstract][Full Text] [Related]
8. Deep Convolutional Neural Networks for breast cancer screening.
Chougrad H; Zouaki H; Alheyane O
Comput Methods Programs Biomed; 2018 Apr; 157():19-30. PubMed ID: 29477427
[TBL] [Abstract][Full Text] [Related]
9. Efficient Breast Cancer Diagnosis from Complex Mammographic Images Using Deep Convolutional Neural Network.
Rahman H; Naik Bukht TF; Ahmad R; Almadhor A; Javed AR
Comput Intell Neurosci; 2023; 2023():7717712. PubMed ID: 36909966
[TBL] [Abstract][Full Text] [Related]
10. Multi-scale attention-based convolutional neural network for classification of breast masses in mammograms.
Niu J; Li H; Zhang C; Li D
Med Phys; 2021 Jul; 48(7):3878-3892. PubMed ID: 33982807
[TBL] [Abstract][Full Text] [Related]
11. YOLO Based Breast Masses Detection and Classification in Full-Field Digital Mammograms.
Aly GH; Marey M; El-Sayed SA; Tolba MF
Comput Methods Programs Biomed; 2021 Mar; 200():105823. PubMed ID: 33190942
[TBL] [Abstract][Full Text] [Related]
12. MOB-CBAM: A dual-channel attention-based deep learning generalizable model for breast cancer molecular subtypes prediction using mammograms.
Nissar I; Alam S; Masood S; Kashif M
Comput Methods Programs Biomed; 2024 May; 248():108121. PubMed ID: 38531147
[TBL] [Abstract][Full Text] [Related]
13. Deep feature-based automatic classification of mammograms.
Arora R; Rai PK; Raman B
Med Biol Eng Comput; 2020 Jun; 58(6):1199-1211. PubMed ID: 32200453
[TBL] [Abstract][Full Text] [Related]
14. Breast cancer diagnosis from contrast-enhanced mammography using multi-feature fusion neural network.
Qian N; Jiang W; Guo Y; Zhu J; Qiu J; Yu H; Huang X
Eur Radiol; 2024 Feb; 34(2):917-927. PubMed ID: 37610440
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network.
Kooi T; van Ginneken B; Karssemeijer N; den Heeten A
Med Phys; 2017 Mar; 44(3):1017-1027. PubMed ID: 28094850
[TBL] [Abstract][Full Text] [Related]
17. A deep learning method for classifying mammographic breast density categories.
Mohamed AA; Berg WA; Peng H; Luo Y; Jankowitz RC; Wu S
Med Phys; 2018 Jan; 45(1):314-321. PubMed ID: 29159811
[TBL] [Abstract][Full Text] [Related]
18. Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography.
Mendel K; Li H; Sheth D; Giger M
Acad Radiol; 2019 Jun; 26(6):735-743. PubMed ID: 30076083
[TBL] [Abstract][Full Text] [Related]
19. Detection of masses in mammograms using a one-stage object detector based on a deep convolutional neural network.
Jung H; Kim B; Lee I; Yoo M; Lee J; Ham S; Woo O; Kang J
PLoS One; 2018; 13(9):e0203355. PubMed ID: 30226841
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]