{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T00:52:09Z","timestamp":1775868729312,"version":"3.50.1"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319469751","type":"print"},{"value":"9783319469768","type":"electronic"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-46976-8_14","type":"book-chapter","created":{"date-parts":[[2016,9,25]],"date-time":"2016-09-25T23:43:16Z","timestamp":1474846996000},"page":"130-141","source":"Crossref","is-referenced-by-count":23,"title":["Fully Automating Graf\u2019s Method for DDH Diagnosis Using Deep Convolutional Neural Networks"],"prefix":"10.1007","author":[{"name":"on\u00a0behalf\u00a0of CUDL","sequence":"first","affiliation":[]},{"given":"David","family":"Golan","sequence":"first","affiliation":[]},{"given":"Yoni","family":"Donner","sequence":"additional","affiliation":[]},{"given":"Chris","family":"Mansi","sequence":"additional","affiliation":[]},{"given":"Jacob","family":"Jaremko","sequence":"additional","affiliation":[]},{"given":"Manoj","family":"Ramachandran","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,9,27]]},"reference":[{"issue":"4","key":"14_CR1","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1302\/0301-620X.83B4.11223","volume":"83","author":"O Furnes","year":"2001","unstructured":"Furnes, O., Lie, S.A., Espehaug, B., Vollset, S.E., Engesaeter, L.B., Havelin, L.I.: Hip disease and the prognosis of total hip replacements. Bone Joint J. 83(4), 579\u2013579 (2001)","journal-title":"Bone Joint J."},{"issue":"2","key":"14_CR2","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/BF00450934","volume":"97","author":"R Graf","year":"1980","unstructured":"Graf, R.: The diagnosis of congenital hip-joint dislocation by the ultrasonic combound treatment. Arch. Orthop. Trauma. Surg. 97(2), 117\u2013133 (1980)","journal-title":"Arch. Orthop. Trauma. Surg."},{"issue":"3","key":"14_CR3","first-page":"479","volume":"75","author":"JJ Dias","year":"1993","unstructured":"Dias, J.J., Thomas, I.H., Lamont, A.C., Mody, B.S., et al.: The reliability of ultrasonographic assessment of neonatal hips. Bone Joint J. 75(3), 479\u2013482 (1993)","journal-title":"Bone Joint J."},{"issue":"5","key":"14_CR4","first-page":"726","volume":"85","author":"EA Roovers","year":"2003","unstructured":"Roovers, E.A., Boere-Boonekamp, M.M., Geertsma, T.S.A., Zielhuis, G.A., Kerkhoff, A.H.M.: Ultrasonographic screening for developmental dysplasia of the hip in infants. Bone Joint J. 85(5), 726\u2013730 (2003)","journal-title":"Bone Joint J."},{"key":"14_CR5","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, pp. 1097\u20131105 (2012)"},{"issue":"7553","key":"14_CR6","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","journal-title":"Nature"},{"key":"14_CR7","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1016\/j.neuroimage.2014.12.061","volume":"108","author":"W Zhang","year":"2015","unstructured":"Zhang, W., Li, R., Deng, H., Wang, L., Lin, W., Ji, S., Shen, D.: Deep convolutional neural networks for multi-modality isointense infant brain image segmentation. NeuroImage 108, 214\u2013224 (2015)","journal-title":"NeuroImage"},{"key":"14_CR8","doi-asserted-by":"crossref","unstructured":"Havaei, M., Davy, A., Warde-Farley, D., Biard, A., Courville, A., Bengio, Y., Pal, C., Jodoin, P.-M., Larochelle, H.: Brain tumor segmentation with deep neural networks. Med. Image Anal. (2016)","DOI":"10.1016\/j.media.2016.05.004"},{"key":"14_CR9","doi-asserted-by":"publisher","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431\u20133440 (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"14_CR10","doi-asserted-by":"publisher","unstructured":"Hariharan, B., Arbel\u00e1ez, P., Girshick, R., Malik, J.: Hypercolumns for object segmentation and fine-grained localization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 447\u2013456 (2015)","DOI":"10.1109\/CVPR.2015.7298642"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Newell, A., Yang, K., Deng, J.: Stacked hourglass networks for human pose estimation. arXiv preprint arXiv:1603.06937 (2016)","DOI":"10.1007\/978-3-319-46484-8_29"},{"key":"14_CR12","unstructured":"Ioffe, S., Szegedy, C., Normalization, B.: Accelerating Deep Network Training by Reducing Internal Covariate Shift. arXiv:1502.03167 , pp. 1\u201311 (2015)"},{"key":"14_CR13","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M.: Generative Adversarial Networks, arXiv preprint, pp. 1\u20139 (2014)"},{"key":"14_CR14","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. arXiv, pp. 1\u201315 (2015)"},{"key":"14_CR15","unstructured":"Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M., et al.: TensorFlow: large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467 (2016)"},{"key":"14_CR16","unstructured":"Kingma, D.P., Ba, J.L.: Adam: a method for stochastic optimization. In: International Conference on Learning Representations, pp. 1\u201313 (2015)"},{"key":"14_CR17","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification. arXiv preprint, pp. 1\u201311 (2015)","DOI":"10.1109\/ICCV.2015.123"},{"key":"14_CR18","doi-asserted-by":"publisher","first-page":"e453","DOI":"10.7717\/peerj.453","volume":"2","author":"S Van der Walt","year":"2014","unstructured":"Van der Walt, S., Sch\u00f6nberger, J.L., Nunez-Iglesias, J., Boulogne, F., Warner, J.D., Yager, N., Gouillart, E., Yu, T.: Scikit-image: image processing in Python. PeerJ 2, e453 (2014)","journal-title":"PeerJ"},{"issue":"6","key":"14_CR19","doi-asserted-by":"publisher","first-page":"488","DOI":"10.1007\/BF02387963","volume":"16","author":"M Zieger","year":"1986","unstructured":"Zieger, M.: Ultrasound of the infant hip. Part 2. Validity of the method. Pediatr. Radiol. 16(6), 488\u2013492 (1986)","journal-title":"Pediatr. Radiol."},{"issue":"2","key":"14_CR20","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1166\/jmihi.2016.1722","volume":"6","author":"KK Cevik","year":"2016","unstructured":"Cevik, K.K., Kocer, H.E., Andac, S.: Segmentation of the ilium and femur regions from ultrasound images for diagnosis of developmental dysplasia of the hip. J. Med. Imaging Health Inf. 6(2), 449\u2013457 (2016)","journal-title":"J. Med. Imaging Health Inf."}],"container-title":["Lecture Notes in Computer Science","Deep Learning and Data Labeling for Medical Applications"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-46976-8_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T20:28:30Z","timestamp":1568406510000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-46976-8_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319469751","9783319469768"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-46976-8_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016]]}}}