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Accurate computing, analysis and modeling of the ventricles and myocardium from medical images are important, especially in the diagnosis and treatment management for patients suffering from myocardial infarction (MI).
Contrast-enhanced MRI and routine single photon emission computed tomography (SPECT) perfusion imaging for detection of subendocardial myocardial infarcts: an imaging study
Wagner, A., Mahrholdt, H., Holly, T.A., Elliott, M.D., Regenfus, M., Parker, M., Klocke, F.J., Bonow, R.O., Kim, R.J., Judd, R.M., 2003 · 2003
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Accurate and objective infarct sizing by contrast-enhanced magnetic resonance imaging in a canine myocardial infarction model
Amado, L.C., Gerber, B.L., Gupta, S.N., Rettmann, D.W., Szarf, G., Schock, R., Nasir, K., Kraitchman, D.L., Lima, J.A., 2004 · 2004
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Quantification of delayed enhancement MR images, in: Medical Image Computing and Computer-Assisted Intervention, pp. 250–257
Dikici, E., O’Donnell, T., Setser, R., White, R., 2004 · 2004
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Shape-based averaging
Rohlfing, T., Maurer, C.R., 2006 · 2006
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User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability
Yushkevich, P.A., Piven, J., Hazlett, H.C., Smith, R.G., Ho, S., Gee, J.C., Gerig, G., 2006 · 2006
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Universal definition of myocardial infarction
Thygesen, K., Alpert, J.S., White, H.D., 2008 · 2008
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Evaluation framework for algorithms segmenting short axis cardiac MRI
Radau, P., Lu, Y., Connelly, K., Paul, G., Dick, A., Wright, G., 2009 · 2009
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Evaluation of techniques for the quantification of myocardial scar of differing etiology using cardiac magnetic resonance
Flett, A.S., Hasleton, J., Cook, C., Hausenloy, D., Quarta, G., Ariti, C., Muthurangu, V., Moon, J.C., 2011 · 2011
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Left ventricular segmentation challenge from cardiac MRI: a collation study, in: International Workshop on Statistical Atlases and Computational Models of the Heart, pp. 88–97
Suinesiaputra, A., Cowan, B.R., Finn, J.P., Fonseca, C.G., Kadish, A.H., Lee, D.C., Medrano-Gracia, P., Warfield, S.K., Tao, W., Young, A.A., 2011 · 2011
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Evaluation of current algorithms for segmentation of scar tissue from late gadolinium enhancement cardiovascular magnetic resonance of the left atrium: an open-access grand challenge
Karim, R., Housden, R.J., Balasubramaniam, M., Chen, Z., Perry, D., Uddin, A., Al-Beyatti, Y., Palkhi, E., Acheampong, P., Obom, S., et al., 2013 · 2013
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Automatic myocardium segmentation of LGE MRI by deformable models with prior shape data
Lu, Y.L., Wright, G., Radau, P.E., 2013 · 2013
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Three-dimensional segmentation of the left ventricle in late gadolinium enhanced MR images of chronic infarction combining long- and short-axis information
Wei, D., Sun, Y., Ong, S.H., Chai, P., Teo, L.L., Low, A.F., 2013 · 2013
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Challenges and methodologies of fully automatic whole heart segmentation: A review
Zhuang, X., 2013 · 2013
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Myocardium segmentation combining T2 and DE MRI using multi-component bivariate gaussian mixture model, in: 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), IEEE. pp. 886–889
Liu, J., Zhuang, X., Liu, J., Zhang, S., Wang, G., Wu, L., Xu, J., Gu, L., 2014 · 2014
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Right ventricle segmentation from cardiac MRI: a collation study
Petitjean, C., Zuluaga, M.A., Bai, W., Dacher, J.N., Grosgeorge, D., Caudron, J., Ruan, S., Ayed, I.B., Cardoso, M.J., Chen, H.C., et al., 2015 · 2015
Cited alongside, same era.
Automated left ventricle segmentation in late gadolinium-enhanced MRI for objective myocardial scar assessment
Tao, Q., Piers, S.R., Lamb, H.J., Rj, V.D.G., 2015 · 2015
Cited alongside, same era.
Benchmark for algorithms segmenting the left atrium from 3D CT and MRI datasets
Tobon-Gomez, C., Geers, A.J., Peters, J., Weese, J., Pinto, K., Karim, R., Ammar, M., Daoudi, A., Margeta, J., Sandoval, Z., et al., 2015 · 2015
Cited alongside, same era.
Deep residual learning for image recognition, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770–778
He, K., Zhang, X., Ren, S., Sun, J., 2016 · 2016
Cited alongside, same era.
Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late gadolinium enhancement MR images
Karim, R., Bhagirath, P., Claus, P., Housden, R.J., Chen, Z., Karimaghaloo, Z., Sohn, H.M., Rodríguez, L.L., Vera, S., Albà, X., et al., 2016 · 2016
Myocardium segmentation from DE MRI with guided random walks and sparse shape representation
Liu, J., Zhuang, X., Xie, H., Zhang, S., Gu, L., 2018 · 2018
Later among the works it cites.
Dilated convolutions in neural networks for left atrial segmentation in 3D gadolinium enhanced-MRI, in: International Workshop on Statistical Atlases and Computational Models of the Heart, Springer. pp. 319–328
Vesal, S., Ravikumar, N., Maier, A., 2018 · 2018
Later among the works it cites.
2018 atrial segmentation challenge
Zhao, J., Xiong, Z., 2018 · 2018
Later among the works it cites.
Selective kernel networks, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 510–519
Li, X., Wang, W., Hu, X., Yang, J., 2019 · 2019
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Multi-sequence myocardium segmentation with cross-constrained shape and neural network-based initialization
Liu, J., Xie, H., Zhang, S., Gu, L., 2019 · 2019
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Cited alongside, same era.
HVSMR 2016: MICCAI workshop on whole-heart and great vessel segmentation from 3D cardiovascular MRI in congenital heart disease
Moghari, M.H., Pace, D.F., Akhondi-Asl, A., Powell, A.J., 2016 · 2016
Cited alongside, same era.
Multivariate mixture model for cardiac segmentation from multi-sequence MRI, in: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer. pp. 581–588
Zhuang, X., 2016 · 2016
Cited alongside, same era.
Myocardium segmentation from DE MRI using multicomponent gaussian mixture model and coupled level set
Liu, J., Zhuang, X., Wu, L., An, D., Xu, J., Peters, T., Gu, L., 2017 · 2017
Cited alongside, same era.
Unpaired image-to-image translation using cycle-consistent adversarial networks, in: Proceedings of the IEEE international conference on computer vision, pp. 2223–2232
Zhu, J.Y., Park, T., Isola, P., Efros, A.A., 2017 · 2017
Cited alongside, same era.
Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?
Bernard, O., Lalande, A., Zotti, C., Cervenansky, F., Yang, X., Heng, P.A., Cetin, I., Lekadir, K., Camara, O., Ballester, M.A.G., et al., 2018 · 2018
Cited alongside, same era.
Squeeze-and-excitation networks, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 7132–7141
Hu, J., Shen, L., Sun, G., 2018 · 2018
Cited alongside, same era.
Multimodal unsupervised image-to-image translation, in: Proceedings of the European Conference on Computer Vision (ECCV), pp. 172–189
Huang, X., Liu, M.Y., Belongie, S., Kautz, J., 2018 · 2018
Cited alongside, same era.
Cardiac segmentation from LGE MRI using deep neural network incorporating shape and spatial priors
Yue, Q., Luo, X., Ye, Q., Xu, L., Zhuang, X., 2019 · 2019
Later among the works it cites.
Multivariate mixture model for myocardial segmentation combining multi-source images
Zhuang, X., 2019 · 2019
Later among the works it cites.
Evaluation of algorithms for multi-modality whole heart segmentation: An open-access grand challenge
Zhuang, X., Li, L., Payer, C., Štern, D., Urschler, M., Heinrich, M.P., Oster, J., Wang, C., Smedby, Ö., Bian, C., et al., 2019 · 2019
Later among the works it cites.
Combining multi-sequence and synthetic images for improved segmentation of late gadolinium enhancement cardiac MRI, in: Pop, M., Sermesant, M., Camara, O., Zhuang, X., Li, S., Young, A., Mansi, T., Suinesiaputra, A. (Eds.), Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, Springer International Publishing, Cham. pp. 290–299
Campello, V.M., Martín-Isla, C., Izquierdo, C., Petersen, S.E., Ballester, M.A.G., Lekadir, K., 2020 · 2020
Closest in time.
An automatic cardiac segmentation framework based on multi-sequence MR image, in: Pop, M., Sermesant, M., Camara, O., Zhuang, X., Li, S., Young, A., Mansi, T., Suinesiaputra, A. (Eds.), Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, Springer International Publishing, Cham. pp. 220–227
Liu, Y., Wang, W., Wang, K., Ye, C., Luo, G., 2020 · 2020
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Style data augmentation for robust segmentation of multi-modality cardiac MRI, in: Pop, M., Sermesant, M., Camara, O., Zhuang, X., Li, S., Young, A., Mansi, T., Suinesiaputra, A. (Eds.), Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, Springer International Publishing, Cham. pp. 197–208
Ly, B., Cochet, H., Sermesant, M., 2020 · 2020
Closest in time.
Cardiac segmentation of LGE MRI with noisy labels, in: Pop, M., Sermesant, M., Camara, O., Zhuang, X., Li, S., Young, A., Mansi, T., Suinesiaputra, A. (Eds.), Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, Springer International Publishing, Cham. pp. 228–236
Roth, H., Zhu, W., Yang, D., Xu, Z., Xu, D., 2020 · 2020
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Automated multi-sequence cardiac mri segmentation using supervised domain adaptation, in: Pop, M., Sermesant, M., Camara, O., Zhuang, X., Li, S., Young, A., Mansi, T., Suinesiaputra, A. (Eds.), Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges, Springer International Publishing, Cham. pp. 300–308
Vesal, S., Ravikumar, N., Maier, A., 2020 · 2020
Closest in time.