538 related articles for article (PubMed ID: 35866492)
1. A VGG attention vision transformer network for benign and malignant classification of breast ultrasound images.
Qu X; Lu H; Tang W; Wang S; Zheng D; Hou Y; Jiang J
Med Phys; 2022 Sep; 49(9):5787-5798. PubMed ID: 35866492
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. An attention-supervised full-resolution residual network for the segmentation of breast ultrasound images.
Qu X; Shi Y; Hou Y; Jiang J
Med Phys; 2020 Nov; 47(11):5702-5714. PubMed ID: 32964449
[TBL] [Abstract][Full Text] [Related]
4. Deep learning-based immunohistochemical estimation of breast cancer via ultrasound image applications.
Yan D; Zhao Z; Duan J; Qu J; Shi L; Wang Q; Zhang H
Front Oncol; 2023; 13():1263685. PubMed ID: 38264739
[TBL] [Abstract][Full Text] [Related]
5. A deep supervised transformer U-shaped full-resolution residual network for the segmentation of breast ultrasound image.
Zhou J; Hou Z; Lu H; Wang W; Zhao W; Wang Z; Zheng D; Wang S; Tang W; Qu X
Med Phys; 2023 Dec; 50(12):7513-7524. PubMed ID: 37816131
[TBL] [Abstract][Full Text] [Related]
6. Distilling Knowledge From an Ensemble of Vision Transformers for Improved Classification of Breast Ultrasound.
Zhou G; Mosadegh B
Acad Radiol; 2024 Jan; 31(1):104-120. PubMed ID: 37666747
[TBL] [Abstract][Full Text] [Related]
7. Classification of multi-feature fusion ultrasound images of breast tumor within category 4 using convolutional neural networks.
Xu P; Zhao J; Wan M; Song Q; Su Q; Wang D
Med Phys; 2024 Jun; 51(6):4243-4257. PubMed ID: 38436433
[TBL] [Abstract][Full Text] [Related]
8. Spatial and geometric learning for classification of breast tumors from multi-center ultrasound images: a hybrid learning approach.
Ru J; Zhu Z; Shi J
BMC Med Imaging; 2024 Jun; 24(1):133. PubMed ID: 38840240
[TBL] [Abstract][Full Text] [Related]
9. BUS-Set: A benchmark for quantitative evaluation of breast ultrasound segmentation networks with public datasets.
Thomas C; Byra M; Marti R; Yap MH; Zwiggelaar R
Med Phys; 2023 May; 50(5):3223-3243. PubMed ID: 36794706
[TBL] [Abstract][Full Text] [Related]
10. CAM-QUS guided self-tuning modular CNNs with multi-loss functions for fully automated breast lesion classification in ultrasound images.
Tasnim J; Hasan MK
Phys Med Biol; 2023 Dec; 69(1):. PubMed ID: 38056017
[No Abstract] [Full Text] [Related]
11. Squeeze-and-excitation-attention-based mobile vision transformer for grading recognition of bladder prolapse in pelvic MRI images.
Zhu S; Chen G; Chen H; Lu Y; Wu M; Zheng B; Liu D; Qian C; Chen Y
Med Phys; 2024 May; ():. PubMed ID: 38767532
[TBL] [Abstract][Full Text] [Related]
12. An Edge-Based Selection Method for Improving Regions-of-Interest Localizations Obtained Using Multiple Deep Learning Object-Detection Models in Breast Ultrasound Images.
Daoud MI; Al-Ali A; Alazrai R; Al-Najar MS; Alsaify BA; Ali MZ; Alouneh S
Sensors (Basel); 2022 Sep; 22(18):. PubMed ID: 36146070
[TBL] [Abstract][Full Text] [Related]
13. Vision Transformers for Classification of Breast Ultrasound Images.
Gheflati B; Rivaz H
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():480-483. PubMed ID: 36086171
[TBL] [Abstract][Full Text] [Related]
14. FMRNet: A fused network of multiple tumoral regions for breast tumor classification with ultrasound images.
Cui W; Peng Y; Yuan G; Cao W; Cao Y; Lu Z; Ni X; Yan Z; Zheng J
Med Phys; 2022 Jan; 49(1):144-157. PubMed ID: 34766623
[TBL] [Abstract][Full Text] [Related]
15. Gray-to-color image conversion in the classification of breast lesions on ultrasound using pre-trained deep neural networks.
Gómez-Flores W; Pereira WCA
Med Biol Eng Comput; 2023 Dec; 61(12):3193-3207. PubMed ID: 37713158
[TBL] [Abstract][Full Text] [Related]
16. Breast Cancer Classification in Automated Breast Ultrasound Using Multiview Convolutional Neural Network with Transfer Learning.
Wang Y; Choi EJ; Choi Y; Zhang H; Jin GY; Ko SB
Ultrasound Med Biol; 2020 May; 46(5):1119-1132. PubMed ID: 32059918
[TBL] [Abstract][Full Text] [Related]
17. Automatic tumor segmentation in breast ultrasound images using a dilated fully convolutional network combined with an active contour model.
Hu Y; Guo Y; Wang Y; Yu J; Li J; Zhou S; Chang C
Med Phys; 2019 Jan; 46(1):215-228. PubMed ID: 30374980
[TBL] [Abstract][Full Text] [Related]
18. A Deep Learning-Based Approach for Cervical Cancer Classification Using 3D CNN and Vision Transformer.
K A; B S
J Imaging Inform Med; 2024 Feb; 37(1):280-296. PubMed ID: 38343216
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Breast Ultrasound Tumor Classification Using a Hybrid Multitask CNN-Transformer Network.
Shareef B; Xian M; Vakanski A; Wang H
Med Image Comput Comput Assist Interv; 2023 Oct; 14223():344-353. PubMed ID: 38601088
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
