554 related articles for article (PubMed ID: 33190942)
1. 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]
2. 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]
3. 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]
4. 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]
5. YOLO-LOGO: A transformer-based YOLO segmentation model for breast mass detection and segmentation in digital mammograms.
Su Y; Liu Q; Xie W; Hu P
Comput Methods Programs Biomed; 2022 Jun; 221():106903. PubMed ID: 35636358
[TBL] [Abstract][Full Text] [Related]
6. Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms.
Al-Antari MA; Han SM; Kim TS
Comput Methods Programs Biomed; 2020 Nov; 196():105584. PubMed ID: 32554139
[TBL] [Abstract][Full Text] [Related]
7. Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram.
Al-Antari MA; Al-Masni MA; Kim TS
Adv Exp Med Biol; 2020; 1213():59-72. PubMed ID: 32030663
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Early detection and classification of abnormality in prior mammograms using image-to-image translation and YOLO techniques.
Baccouche A; Garcia-Zapirain B; Zheng Y; Elmaghraby AS
Comput Methods Programs Biomed; 2022 Jun; 221():106884. PubMed ID: 35594582
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Deep learning for mass detection in Full Field Digital Mammograms.
Agarwal R; Díaz O; Yap MH; Lladó X; Martí R
Comput Biol Med; 2020 Jun; 121():103774. PubMed ID: 32339095
[TBL] [Abstract][Full Text] [Related]
12. A deep learning approach for the analysis of masses in mammograms with minimal user intervention.
Dhungel N; Carneiro G; Bradley AP
Med Image Anal; 2017 Apr; 37():114-128. PubMed ID: 28171807
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. 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]
15. Automatic Breast Mass Segmentation and Classification Using Subtraction of Temporally Sequential Digital Mammograms.
Loizidou K; Skouroumouni G; Nikolaou C; Pitris C
IEEE J Transl Eng Health Med; 2022; 10():1801111. PubMed ID: 36519002
[TBL] [Abstract][Full Text] [Related]
16. Identification and Classification of Benign and Malignant Masses based on Subtraction of Temporally Sequential Digital Mammograms.
Loizidou K; Skouroumouni G; Savvidou G; Constantinidou A; Nikolaou C; Pitris C
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():1667-1670. PubMed ID: 36085665
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. A YOLO-based AI system for classifying calcifications on spot magnification mammograms.
Chen JL; Cheng LH; Wang J; Hsu TW; Chen CY; Tseng LM; Guo SM
Biomed Eng Online; 2023 May; 22(1):54. PubMed ID: 37237394
[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. Breast mass detection and diagnosis using fused features with density.
Wang Z; Huang Y; Li M; Zhang H; Li C; Xin J; Qian W
J Xray Sci Technol; 2019; 27(2):321-342. PubMed ID: 30856154
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
