733 related articles for article (PubMed ID: 33485057)
1. 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]
2. Fully automated cardiac MRI segmentation using dilated residual network.
Ahmad F; Hou W; Xiong J; Xia Z
Med Phys; 2023 Apr; 50(4):2162-2175. PubMed ID: 36395472
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Fully Automatic initialization and segmentation of left and right ventricles for large-scale cardiac MRI using a deeply supervised network and 3D-ASM.
Hu H; Pan N; Frangi AF
Comput Methods Programs Biomed; 2023 Oct; 240():107679. PubMed ID: 37364366
[TBL] [Abstract][Full Text] [Related]
5. A distance map regularized CNN for cardiac cine MR image segmentation.
Dangi S; Linte CA; Yaniv Z
Med Phys; 2019 Dec; 46(12):5637-5651. PubMed ID: 31598971
[TBL] [Abstract][Full Text] [Related]
6. Fully automated segmentation of the left ventricle in cine cardiac MRI using neural network regression.
Tan LK; McLaughlin RA; Lim E; Abdul Aziz YF; Liew YM
J Magn Reson Imaging; 2018 Jul; 48(1):140-152. PubMed ID: 29316024
[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. Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using ensemble of classifiers.
Khened M; Kollerathu VA; Krishnamurthi G
Med Image Anal; 2019 Jan; 51():21-45. PubMed ID: 30390512
[TBL] [Abstract][Full Text] [Related]
9. Left ventricle automatic segmentation in cardiac MRI using a combined CNN and U-net approach.
Wu B; Fang Y; Lai X
Comput Med Imaging Graph; 2020 Jun; 82():101719. PubMed ID: 32325284
[TBL] [Abstract][Full Text] [Related]
10. SAUN: Stack attention U-Net for left ventricle segmentation from cardiac cine magnetic resonance imaging.
Sun X; Garg P; Plein S; van der Geest RJ
Med Phys; 2021 Apr; 48(4):1750-1763. PubMed ID: 33544895
[TBL] [Abstract][Full Text] [Related]
11. Segmentation of Cardiac Structures via Successive Subspace Learning with Saab Transform from Cine MRI.
Liu X; Xing F; Gaggin HK; Wang W; Kuo CJ; El Fakhri G; Woo J
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3535-3538. PubMed ID: 34892002
[TBL] [Abstract][Full Text] [Related]
12. Automated Cardiovascular Pathology Assessment Using Semantic Segmentation and Ensemble Learning.
Lindsey T; Lee JJ
J Digit Imaging; 2020 Jun; 33(3):607-612. PubMed ID: 31939003
[TBL] [Abstract][Full Text] [Related]
13. Cardiac Disease Classification Using Two-Dimensional Thickness and Few-Shot Learning Based on Magnetic Resonance Imaging Image Segmentation.
Wibowo A; Triadyaksa P; Sugiharto A; Sarwoko EA; Nugroho FA; Arai H; Kawakubo M
J Imaging; 2022 Jul; 8(7):. PubMed ID: 35877637
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. A deep learning-based approach for automatic segmentation and quantification of the left ventricle from cardiac cine MR images.
Abdeltawab H; Khalifa F; Taher F; Alghamdi NS; Ghazal M; Beache G; Mohamed T; Keynton R; El-Baz A
Comput Med Imaging Graph; 2020 Apr; 81():101717. PubMed ID: 32222684
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach.
Lavdas I; Glocker B; Kamnitsas K; Rueckert D; Mair H; Sandhu A; Taylor SA; Aboagye EO; Rockall AG
Med Phys; 2017 Oct; 44(10):5210-5220. PubMed ID: 28756622
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Cine MRI analysis by deep learning of optical flow: Adding the temporal dimension.
Yan W; Wang Y; van der Geest RJ; Tao Q
Comput Biol Med; 2019 Aug; 111():103356. PubMed ID: 31323604
[TBL] [Abstract][Full Text] [Related]
20. A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.
Avendi MR; Kheradvar A; Jafarkhani H
Med Image Anal; 2016 May; 30():108-119. PubMed ID: 26917105
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]