These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
309 related articles for article (PubMed ID: 33285484)
1. Fully automated left atrium segmentation from anatomical cine long-axis MRI sequences using deep convolutional neural network with unscented Kalman filter. Zhang X; Noga M; Martin DG; Punithakumar K Med Image Anal; 2021 Feb; 68():101916. PubMed ID: 33285484 [TBL] [Abstract][Full Text] [Related]
2. Assessment of Bi-Ventricular and Bi-Atrial Areas Using Four-Chamber Cine Cardiovascular Magnetic Resonance Imaging: Fully Automated Segmentation with a U-Net Convolutional Neural Network. Arai H; Kawakubo M; Sanui K; Iwamoto R; Nishimura H; Kadokami T Int J Environ Res Public Health; 2022 Jan; 19(3):. PubMed ID: 35162424 [TBL] [Abstract][Full Text] [Related]
3. GCW-UNet segmentation of cardiac magnetic resonance images for evaluation of left atrial enlargement. Wong KKL; Zhang A; Yang K; Wu S; Ghista DN Comput Methods Programs Biomed; 2022 Jun; 221():106915. PubMed ID: 35653942 [TBL] [Abstract][Full Text] [Related]
4. Automated left and right ventricular chamber segmentation in cardiac magnetic resonance images using dense fully convolutional neural network. Penso M; Moccia S; Scafuri S; Muscogiuri G; Pontone G; Pepi M; Caiani EG Comput Methods Programs Biomed; 2021 Jun; 204():106059. PubMed ID: 33812305 [TBL] [Abstract][Full Text] [Related]
5. Automatic cardiac cine MRI segmentation and heart disease classification. Ammar A; Bouattane O; Youssfi M Comput Med Imaging Graph; 2021 Mar; 88():101864. PubMed ID: 33485057 [TBL] [Abstract][Full Text] [Related]
6. Evaluation of fully automated myocardial segmentation techniques in native and contrast-enhanced T1-mapping cardiovascular magnetic resonance images using fully convolutional neural networks. Farrag NA; Lochbihler A; White JA; Ukwatta E Med Phys; 2021 Jan; 48(1):215-226. PubMed ID: 33131085 [TBL] [Abstract][Full Text] [Related]
7. Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture. Qin W; Wu Y; Li S; Chen Y; Yang Y; Liu X; Zheng H; Liang D; Hu Z Biomed Phys Eng Express; 2020 Feb; 6(2):025009. PubMed ID: 33438635 [TBL] [Abstract][Full Text] [Related]
8. Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images. Tong N; Gou S; Yang S; Cao M; Sheng K Med Phys; 2019 Jun; 46(6):2669-2682. PubMed ID: 31002188 [TBL] [Abstract][Full Text] [Related]
9. Automated segmentation of long and short axis DENSE cardiovascular magnetic resonance for myocardial strain analysis using spatio-temporal convolutional neural networks. Barbaroux H; Kunze KP; Neji R; Nazir MS; Pennell DJ; Nielles-Vallespin S; Scott AD; Young AA J Cardiovasc Magn Reson; 2023 Mar; 25(1):16. PubMed ID: 36991474 [TBL] [Abstract][Full Text] [Related]
10. An iterative multi-path fully convolutional neural network for automatic cardiac segmentation in cine MR images. Ma Z; Wu X; Wang X; Song Q; Yin Y; Cao K; Wang Y; Zhou J Med Phys; 2019 Dec; 46(12):5652-5665. PubMed ID: 31605627 [TBL] [Abstract][Full Text] [Related]
11. Deep morphology aided diagnosis network for segmentation of carotid artery vessel wall and diagnosis of carotid atherosclerosis on black-blood vessel wall MRI. Wu J; Xin J; Yang X; Sun J; Xu D; Zheng N; Yuan C Med Phys; 2019 Dec; 46(12):5544-5561. PubMed ID: 31356693 [TBL] [Abstract][Full Text] [Related]
12. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks. Tong N; Gou S; Yang S; Ruan D; Sheng K Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285 [TBL] [Abstract][Full Text] [Related]
13. Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks. Vigneault DM; Xie W; Ho CY; Bluemke DA; Noble JA Med Image Anal; 2018 Aug; 48():95-106. PubMed ID: 29857330 [TBL] [Abstract][Full Text] [Related]
14. A novel U-Net approach to segment the cardiac chamber in magnetic resonance images with ghost artifacts. Zhao M; Wei Y; Lu Y; Wong KKL Comput Methods Programs Biomed; 2020 Nov; 196():105623. PubMed ID: 32652355 [TBL] [Abstract][Full Text] [Related]
15. Healthy Kidney Segmentation in the Dce-Mr Images Using a Convolutional Neural Network and Temporal Signal Characteristics. Klepaczko A; Eikefjord E; Lundervold A Sensors (Basel); 2021 Oct; 21(20):. PubMed ID: 34695931 [TBL] [Abstract][Full Text] [Related]
16. End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions. Pérez-Pelegrí M; Monmeneu JV; López-Lereu MP; Maceira AM; Bodi V; Moratal D Comput Med Imaging Graph; 2022 Jul; 99():102085. PubMed ID: 35689982 [TBL] [Abstract][Full Text] [Related]
17. Automated magnetic resonance image segmentation of the anterior cruciate ligament. Flannery SW; Kiapour AM; Edgar DJ; Murray MM; Fleming BC J Orthop Res; 2021 Apr; 39(4):831-840. PubMed ID: 33241856 [TBL] [Abstract][Full Text] [Related]
18. A bidirectional registration neural network for cardiac motion tracking using cine MRI images. Lu J; Jin R; Wang M; Song E; Ma G Comput Biol Med; 2023 Jun; 160():107001. PubMed ID: 37187138 [TBL] [Abstract][Full Text] [Related]
19. An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets. Fashandi H; Kuling G; Lu Y; Wu H; Martel AL Med Phys; 2019 Mar; 46(3):1230-1244. PubMed ID: 30609062 [TBL] [Abstract][Full Text] [Related]
20. Dynamic pixel-wise weighting-based fully convolutional neural networks for left ventricle segmentation in short-axis MRI. Wang Z; Xie L; Qi J Magn Reson Imaging; 2020 Feb; 66():131-140. PubMed ID: 31465788 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]