194 related articles for article (PubMed ID: 28762196)
1. Ultrasound image-based thyroid nodule automatic segmentation using convolutional neural networks.
Ma J; Wu F; Jiang T; Zhao Q; Kong D
Int J Comput Assist Radiol Surg; 2017 Nov; 12(11):1895-1910. PubMed ID: 28762196
[TBL] [Abstract][Full Text] [Related]
2. SK-Unet++: An improved Unet++ network with adaptive receptive fields for automatic segmentation of ultrasound thyroid nodule images.
Dai H; Xie W; Xia E
Med Phys; 2024 Mar; 51(3):1798-1811. PubMed ID: 37606374
[TBL] [Abstract][Full Text] [Related]
3. FDE-net: Frequency-domain enhancement network using dynamic-scale dilated convolution for thyroid nodule segmentation.
Chen H; Yu MA; Chen C; Zhou K; Qi S; Chen Y; Xiao R
Comput Biol Med; 2023 Feb; 153():106514. PubMed ID: 36628913
[TBL] [Abstract][Full Text] [Related]
4. MLMSeg: A multi-view learning model for ultrasound thyroid nodule segmentation.
Chen G; Tan G; Duan M; Pu B; Luo H; Li S; Li K
Comput Biol Med; 2024 Feb; 169():107898. PubMed ID: 38176210
[TBL] [Abstract][Full Text] [Related]
5. Semi-supervised graph convolutional networks for the domain adaptive recognition of thyroid nodules in cross-device ultrasound images.
Zhang K; Li Z; Cai C; Liu J; Xu D; Fang C; Huang P; Wang Y; Yang M; Chang S
Med Phys; 2023 Dec; 50(12):7806-7821. PubMed ID: 36967664
[TBL] [Abstract][Full Text] [Related]
6. Shape-margin knowledge augmented network for thyroid nodule segmentation and diagnosis.
Liu W; Lin C; Chen D; Niu L; Zhang R; Pi Z
Comput Methods Programs Biomed; 2024 Feb; 244():107999. PubMed ID: 38194766
[TBL] [Abstract][Full Text] [Related]
7. Automatic Recognition and Classification System of Thyroid Nodules in CT Images Based on CNN.
Li W; Cheng S; Qian K; Yue K; Liu H
Comput Intell Neurosci; 2021; 2021():5540186. PubMed ID: 34135949
[TBL] [Abstract][Full Text] [Related]
8. Joint Detection of Tap and CEA Based on Deep Learning Medical Image Segmentation: Risk Prediction of Thyroid Cancer.
Lang S; Xu Y; Li L; Wang B; Yang Y; Xue Y; Shi K
J Healthc Eng; 2021; 2021():5920035. PubMed ID: 34158913
[TBL] [Abstract][Full Text] [Related]
9. Real-time reliable semantic segmentation of thyroid nodules in ultrasound images.
Xing G; Wang S; Gao J; Li X
Phys Med Biol; 2024 Jan; 69(2):. PubMed ID: 38048630
[No Abstract] [Full Text] [Related]
10. Densely connected convolutional networks for ultrasound image based lesion segmentation.
Ma J; Kong D; Wu F; Bao L; Yuan J; Liu Y
Comput Biol Med; 2024 Jan; 168():107725. PubMed ID: 38006827
[TBL] [Abstract][Full Text] [Related]
11. Fully‑automated deep‑learning segmentation of pediatric cardiovascular magnetic resonance of patients with complex congenital heart diseases.
Karimi-Bidhendi S; Arafati A; Cheng AL; Wu Y; Kheradvar A; Jafarkhani H
J Cardiovasc Magn Reson; 2020 Nov; 22(1):80. PubMed ID: 33256762
[TBL] [Abstract][Full Text] [Related]
12. An intelligent platform for ultrasound diagnosis of thyroid nodules.
Ye H; Hang J; Chen X; Di Xu ; Chen J; Ye X; Zhang D
Sci Rep; 2020 Aug; 10(1):13223. PubMed ID: 32764673
[TBL] [Abstract][Full Text] [Related]
13. Thyroid ultrasound diagnosis improvement via multi-view self-supervised learning and two-stage pre-training.
Wang J; Yang X; Jia X; Xue W; Chen R; Chen Y; Zhu X; Liu L; Cao Y; Zhou J; Ni D; Gu N
Comput Biol Med; 2024 Mar; 171():108087. PubMed ID: 38364658
[TBL] [Abstract][Full Text] [Related]
14. An efficient framework for lesion segmentation in ultrasound images using global adversarial learning and region-invariant loss.
Manh V; Jia X; Xue W; Xu W; Mei Z; Dong Y; Zhou J; Huang R; Ni D
Comput Biol Med; 2024 Mar; 171():108137. PubMed ID: 38447499
[TBL] [Abstract][Full Text] [Related]
15. Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.
Wang S; Zhou M; Liu Z; Liu Z; Gu D; Zang Y; Dong D; Gevaert O; Tian J
Med Image Anal; 2017 Aug; 40():172-183. PubMed ID: 28688283
[TBL] [Abstract][Full Text] [Related]
16. Cascade and Fusion of Multitask Convolutional Neural Networks for Detection of Thyroid Nodules in Contrast-Enhanced CT.
Zhao Z; Ye C; Hu Y; Li C; Li X
Comput Intell Neurosci; 2019; 2019():7401235. PubMed ID: 31781181
[TBL] [Abstract][Full Text] [Related]
17. Automated Segmentation of Thyroid Nodule, Gland, and Cystic Components From Ultrasound Images Using Deep Learning.
Kumar V; Webb J; Gregory A; Meixner DD; Knudsen JM; Callstrom M; Fatemi M; Alizad A
IEEE Access; 2020; 8():63482-63496. PubMed ID: 32995106
[TBL] [Abstract][Full Text] [Related]
18. Hybrid CNN-transformer network for interactive learning of challenging musculoskeletal images.
Bi L; Buehner U; Fu X; Williamson T; Choong P; Kim J
Comput Methods Programs Biomed; 2024 Jan; 243():107875. PubMed ID: 37871450
[TBL] [Abstract][Full Text] [Related]
19. Application Value of a Deep Convolutional Neural Network Model for Cytological Assessment of Thyroid Nodules.
Ren Y; He Y; Cong L
J Healthc Eng; 2021; 2021():6076135. PubMed ID: 34795882
[TBL] [Abstract][Full Text] [Related]
20. Multistep Automated Data Labelling Procedure (MADLaP) for thyroid nodules on ultrasound: An artificial intelligence approach for automating image annotation.
Zhang J; Mazurowski MA; Allen BC; Wildman-Tobriner B
Artif Intell Med; 2023 Jul; 141():102553. PubMed ID: 37295897
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
