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Chapter 2 Deep convolutional neural network in medical image processing  59




               [106] Y. Bar, I. Diamant, L. Wolf, S. Lieberman, E. Konen, H. Greenspan, Chest
                    pathology identification using deep feature selection with non-medical
                    training, Comput. Methods Biomech. Biomed. Eng.: Imaging Vis. 6 (3)
                    (2018) 259e263.
               [107] W. Shen, M. Zhou, F. Yang, D. Dong, C. Yang, Y. Zang, J. Tian, Learning
                    from experts: developing transferable deep features for patient-level lung
                    cancer prediction, in: International Conference on Medical Image
                    Computing and Computer-Assisted Intervention, Springer, Cham, 2016,
                    October, pp. 124e131.
               [108] S. Christodoulidis, M. Anthimopoulos, L. Ebner, A. Christe,
                    S. Mougiakakou, Multisource transfer learning with convolutional neural
                    networks for lung pattern analysis, IEEE J. Biomed. Health Inform. 21 (1)
                    (2016) 76e84.
               [109] O. Emad, I.A. Yassine, A.S. Fahmy, Automatic localization of the left
                    ventricle in cardiac MRI images using deep learning, in: 2015 37th Annual
                    International Conference of the IEEE Engineering in Medicine and
                    Biology Society (EMBC), IEEE, 2015, August, pp. 683e686.
               [110] M. Zreik, T. Leiner, B.D. De Vos, R.W. van Hamersvelt, M.A. Viergever,
                    I. I  sgum, Automatic segmentation of the left ventricle in cardiac CT
                    angiography using convolutional neural networks, in: 2016 IEEE 13th
                    International Symposium on Biomedical Imaging (ISBI), IEEE, 2016, April,
                    pp. 40e43.
               [111] J.M. Wolterink, T. Leiner, B.D. de Vos, R.W. van Hamersvelt,
                    M.A. Viergever, I. I  sgum, Automatic coronary artery calcium scoring in
                    cardiac CT angiography using paired convolutional neural networks, Med.
                    Image Anal. 34 (2016) 123e136.
               [112] M.A. G€ uls€ un, G. Funka-Lea, P. Sharma, S. Rapaka, Y. Zheng, Coronary
                    centerline extraction via optimal flow paths and CNN path pruning, in:
                    International Conference on Medical Image Computing and Computer-
                    Assisted Intervention, Springer, Cham, 2016, October, pp. 317e325.
               [113] M. Moradi, Y. Gur, H. Wang, P. Prasanna, T. Syeda-Mahmood, A hybrid
                    learning approach for semantic labeling of cardiac CT slices and
                    recognition of body position, in: 2016 IEEE 13th International Symposium
                    on Biomedical Imaging (ISBI), IEEE, 2016, April, pp. 1418e1421.
               [114] H. Chen, Y. Zheng, J.H. Park, P.A. Heng, S.K. Zhou, Iterative multi-domain
                    regularized deep learning for anatomical structure detection and
                    segmentation from ultrasound images, in: International Conference on
                    Medical Image Computing and Computer-Assisted Intervention, Springer,
                    Cham, 2016, October, pp. 487e495.
               [115] L. Zhang, A. Gooya, B. Dong, R. Hua, S.E. Petersen, P. Medrano-Gracia,
                    A.F. Frangi, Automated quality assessment of cardiac MR images using
                    convolutional neural networks, in: International Workshop on Simulation
                    and Synthesis in Medical Imaging, Springer, Cham, 2016, October,
                    pp. 138e145.
               [116] H. Yang, J. Sun, H. Li, L. Wang, Z. Xu, Deep fusion net for multi-atlas
                    segmentation: application to cardiac MR images, in: International
                    Conference on Medical Image Computing and Computer-Assisted
                    Intervention, Springer, Cham, 2016, October, pp. 521e528.
               [117] O. Oktay, W. Bai, M. Lee, R. Guerrero, K. Kamnitsas, J. Caballero, A. de
                    Marvao, S. Cook, D. O'Regan, D. Rueckert, Multi-input cardiac image
                    super-resolution using convolutional neural networks, in: International
                    Conference on Medical Image Computing and Computer-Assisted
                    Intervention, Springer, Cham, 2016, October, pp. 246e254.
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