209 related articles for article (PubMed ID: 34351855)
1. Dual Convolutional Neural Networks for Breast Mass Segmentation and Diagnosis in Mammography.
Li H; Chen D; Nailon WH; Davies ME; Laurenson DI
IEEE Trans Med Imaging; 2022 Jan; 41(1):3-13. PubMed ID: 34351855
[TBL] [Abstract][Full Text] [Related]
2. Convolutional neural network for automated mass segmentation in mammography.
Abdelhafiz D; Bi J; Ammar R; Yang C; Nabavi S
BMC Bioinformatics; 2020 Dec; 21(Suppl 1):192. PubMed ID: 33297952
[TBL] [Abstract][Full Text] [Related]
3. Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset.
Sawyer Lee R; Dunnmon JA; He A; Tang S; Ré C; Rubin DL
J Biomed Inform; 2021 Jan; 113():103656. PubMed ID: 33309994
[TBL] [Abstract][Full Text] [Related]
4. Integrating segmentation information into CNN for breast cancer diagnosis of mammographic masses.
Tsochatzidis L; Koutla P; Costaridou L; Pratikakis I
Comput Methods Programs Biomed; 2021 Mar; 200():105913. PubMed ID: 33422854
[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. 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]
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. SAP-cGAN: Adversarial learning for breast mass segmentation in digital mammogram based on superpixel average pooling.
Li Y; Zhao G; Zhang Q; Lin Y; Wang M
Med Phys; 2021 Mar; 48(3):1157-1167. PubMed ID: 33340125
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. 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]
11. Deep Neural Networks With Region-Based Pooling Structures for Mammographic Image Classification.
Shu X; Zhang L; Wang Z; Lv Q; Yi Z
IEEE Trans Med Imaging; 2020 Jun; 39(6):2246-2255. PubMed ID: 31985411
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. 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]
15. 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]
16. 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]
17. A comparative study of pre-trained convolutional neural networks for semantic segmentation of breast tumors in ultrasound.
Gómez-Flores W; Coelho de Albuquerque Pereira W
Comput Biol Med; 2020 Nov; 126():104036. PubMed ID: 33059238
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. 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]
[Next] [New Search]