472 related articles for article (PubMed ID: 33982807)
1. 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]
2. New convolutional neural network model for screening and diagnosis of mammograms.
Zhang C; Zhao J; Niu J; Li D
PLoS One; 2020; 15(8):e0237674. PubMed ID: 32790772
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. 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; CorrĂȘa Silva A; de Paiva AC; Gattass M
Comput Methods Programs Biomed; 2018 Mar; 156():191-207. PubMed ID: 29428071
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. A Novel Algorithm for Breast Mass Classification in Digital Mammography Based on Feature Fusion.
Zhang Q; Li Y; Zhao G; Man P; Lin Y; Wang M
J Healthc Eng; 2020; 2020():8860011. PubMed ID: 33425311
[TBL] [Abstract][Full Text] [Related]
8. A Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms.
Sarath CK; Chakravarty A; Ghosh N; Sarkar T; Sethuraman R; Sheet D
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1128-1131. PubMed ID: 33018185
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Detection and classification of the breast abnormalities in digital mammograms via regional Convolutional Neural Network.
Al-Masni MA; Al-Antari MA; Park JM; Gi G; Kim TY; Rivera P; Valarezo E; Han SM; Kim TS
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():1230-1233. PubMed ID: 29060098
[TBL] [Abstract][Full Text] [Related]
11. A framework for breast cancer classification using Multi-DCNNs.
Ragab DA; Attallah O; Sharkas M; Ren J; Marshall S
Comput Biol Med; 2021 Apr; 131():104245. PubMed ID: 33556893
[TBL] [Abstract][Full Text] [Related]
12. Improving Performance of Breast Lesion Classification Using a ResNet50 Model Optimized with a Novel Attention Mechanism.
Islam W; Jones M; Faiz R; Sadeghipour N; Qiu Y; Zheng B
Tomography; 2022 Sep; 8(5):2411-2425. PubMed ID: 36287799
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. 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]
15. 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]
16. A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms.
Boumaraf S; Liu X; Ferkous C; Ma X
Biomed Res Int; 2020; 2020():7695207. PubMed ID: 32462017
[TBL] [Abstract][Full Text] [Related]
17. Computer Vision-Based Microcalcification Detection in Digital Mammograms Using Fully Connected Depthwise Separable Convolutional Neural Network.
Rehman KU; Li J; Pei Y; Yasin A; Ali S; Mahmood T
Sensors (Basel); 2021 Jul; 21(14):. PubMed ID: 34300597
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. Using convolutional neural networks to discriminate between cysts and masses in Monte Carlo-simulated dual-energy mammography.
Makeev A; Toner B; Qian M; Badal A; Glick SJ
Med Phys; 2021 Aug; 48(8):4648-4655. PubMed ID: 34050965
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]