304 related articles for article (PubMed ID: 35271746)
1. Feature fusion Siamese network for breast cancer detection comparing current and prior mammograms.
Bai J; Jin A; Wang T; Yang C; Nabavi S
Med Phys; 2022 Jun; 49(6):3654-3669. PubMed ID: 35271746
[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. 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]
4. FSE-Net: feature selection and enhancement network for mammogram classification.
Liao C; Wen X; Qi S; Liu Y; Cao R
Phys Med Biol; 2023 Sep; 68(19):. PubMed ID: 37712226
[No Abstract] [Full Text] [Related]
5. RAMS: Remote and automatic mammogram screening.
Cogan T; Cogan M; Tamil L
Comput Biol Med; 2019 Apr; 107():18-29. PubMed ID: 30771549
[TBL] [Abstract][Full Text] [Related]
6. Role of General Adversarial Networks in Mammogram Analysis: A Review.
Gopal A; Gandhimaruthian L; Ali J
Curr Med Imaging; 2020; 16(7):863-877. PubMed ID: 33059556
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Deep convolutional neural network and emotional learning based breast cancer detection using digital mammography.
Chouhan N; Khan A; Shah JZ; Hussnain M; Khan MW
Comput Biol Med; 2021 May; 132():104318. PubMed ID: 33744608
[TBL] [Abstract][Full Text] [Related]
9. Architectural Distortion-Based Digital Mammograms Classification Using Depth Wise Convolutional Neural Network.
Rehman KU; Li J; Pei Y; Yasin A; Ali S; Saeed Y
Biology (Basel); 2021 Dec; 11(1):. PubMed ID: 35053013
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. Optimized Radial Basis Neural Network for Classification of Breast Cancer Images.
Rajathi GM
Curr Med Imaging; 2021; 17(1):97-108. PubMed ID: 32416697
[TBL] [Abstract][Full Text] [Related]
13. Microcalcification Discrimination in Mammography Using Deep Convolutional Neural Network: Towards Rapid and Early Breast Cancer Diagnosis.
Leong YS; Hasikin K; Lai KW; Mohd Zain N; Azizan MM
Front Public Health; 2022; 10():875305. PubMed ID: 35570962
[TBL] [Abstract][Full Text] [Related]
14. Enhanced breast mass mammography classification approach based on pre-processing and hybridization of transfer learning models.
Boudouh SS; Bouakkaz M
J Cancer Res Clin Oncol; 2023 Nov; 149(16):14549-14564. PubMed ID: 37567987
[TBL] [Abstract][Full Text] [Related]
15. Computer-extracted global radiomic features can predict the radiologists' first impression about the abnormality of a screening mammogram.
Siviengphanom S; Lewis SJ; Brennan PC; Gandomkar Z
Br J Radiol; 2024 Jan; 97(1153):168-179. PubMed ID: 38263826
[TBL] [Abstract][Full Text] [Related]
16. Transfer learning with different modified convolutional neural network models for classifying digital mammograms utilizing Local Dataset.
Mutar MT; Majid M; Ibrahim MJ; Obaid AH; Alsammarraie AZ; Altameemi E; Kareem TF
Gulf J Oncolog; 2023 Jan; 1(41):66-71. PubMed ID: 36804161
[TBL] [Abstract][Full Text] [Related]
17. Classification of Whole Mammogram and Tomosynthesis Images Using Deep Convolutional Neural Networks.
Zhang X; Zhang Y; Han EY; Jacobs N; Han Q; Wang X; Liu J
IEEE Trans Nanobioscience; 2018 Jul; 17(3):237-242. PubMed ID: 29994219
[TBL] [Abstract][Full Text] [Related]
18. Bilateral Analysis Boosts the Performance of Mammography-based Deep Learning Models in Breast Cancer Risk Prediction.
Mohamed A; Fakhry S; Basha T
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():1440-1443. PubMed ID: 36086431
[TBL] [Abstract][Full Text] [Related]
19. Fus2Net: a novel Convolutional Neural Network for classification of benign and malignant breast tumor in ultrasound images.
Ma H; Tian R; Li H; Sun H; Lu G; Liu R; Wang Z
Biomed Eng Online; 2021 Nov; 20(1):112. PubMed ID: 34794443
[TBL] [Abstract][Full Text] [Related]
20. Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms.
Sahu A; Das PK; Meher S
Phys Med; 2023 Oct; 114():103138. PubMed ID: 37914431
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]