{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T17:52:57Z","timestamp":1730310777886,"version":"3.28.0"},"reference-count":8,"publisher":"SPIE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,4,4]]},"DOI":"10.1117\/12.2607655","type":"proceedings-article","created":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T23:45:08Z","timestamp":1648683908000},"page":"49","source":"Crossref","is-referenced-by-count":0,"title":["An iterative approach to efficient deep learning-based CT bone segmentation task"],"prefix":"10.1117","author":[{"given":"Prakhar","family":"Prakash","sequence":"first","affiliation":[]},{"given":"Joseph","family":"Gross","sequence":"additional","affiliation":[]},{"given":"Sandeep","family":"Dutta","sequence":"additional","affiliation":[]}],"member":"189","reference":[{"key":"c1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-03002-7"},{"key":"c2","article-title":"CT Organ Segmentation Using GPU Data Augmentation, Unsupervised Labels and IOU Loss","author":"Rister","year":"2018","journal-title":"ArXiv abs\/1811.11226"},{"key":"c3","article-title":"3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation","author":"\u00c7i\u00e7ek","year":"2016","journal-title":"ArXiv abs\/1606.06650"},{"key":"c4","first-page":"448","article-title":"Batch normalization: accelerating deep network training by reducing internal covariate shift","volume-title":"Proc. ICML","volume":"37","author":"Ioffe","year":"2015"},{"key":"c5","article-title":"Instance Normalization: The Missing Ingredient for Fast Stylization","author":"Ulyanov","year":"2016","journal-title":"ArXiv abs\/1607.08022"},{"key":"c6","article-title":"Group Normalization","author":"Wu","year":"2018","journal-title":"ECCV"},{"key":"c7","article-title":"Layer Normalization","author":"Ba","year":"2016","journal-title":"ArXiv abs\/1607.06450"},{"key":"c8","article-title":"Distance Map Loss Penalty Term for Semantic Segmentation","author":"Caliva","year":"2019","journal-title":"ArXiv abs\/1908.03679"}],"event":{"name":"Biomedical Applications in Molecular, Structural, and Functional Imaging","start":{"date-parts":[[2022,2,20]]},"location":"San Diego, United States","end":{"date-parts":[[2022,3,28]]}},"container-title":["Medical Imaging 2022: Biomedical Applications in Molecular, Structural, and Functional Imaging"],"original-title":[],"deposited":{"date-parts":[[2022,7,3]],"date-time":"2022-07-03T01:35:18Z","timestamp":1656812118000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.spiedigitallibrary.org\/conference-proceedings-of-spie\/12036\/2607655\/An-iterative-approach-to-efficient-deep-learning-based-CT-bone\/10.1117\/12.2607655.full"}},"subtitle":[],"editor":[{"given":"Barjor S.","family":"Gimi","sequence":"additional","affiliation":[]},{"given":"Andrzej","family":"Krol","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2022,4,4]]},"references-count":8,"URL":"https:\/\/doi.org\/10.1117\/12.2607655","relation":{},"subject":[],"published":{"date-parts":[[2022,4,4]]}}}