{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T05:22:03Z","timestamp":1730265723966,"version":"3.28.0"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,7,15]],"date-time":"2020-07-15T00:00:00Z","timestamp":1594771200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,7,15]],"date-time":"2020-07-15T00:00:00Z","timestamp":1594771200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,7,15]],"date-time":"2020-07-15T00:00:00Z","timestamp":1594771200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7,15]]},"DOI":"10.1109\/iisa50023.2020.9284370","type":"proceedings-article","created":{"date-parts":[[2021,4,16]],"date-time":"2021-04-16T13:59:38Z","timestamp":1618581578000},"page":"1-8","source":"Crossref","is-referenced-by-count":1,"title":["Development of Convolutional Neural Networkbased models for bone metastasis classification in nuclear medicine"],"prefix":"10.1109","author":[{"given":"Nikolaos I.","family":"Papandrianos","sequence":"first","affiliation":[]},{"given":"Elpiniki I.","family":"Papageorgiou","sequence":"additional","affiliation":[]},{"given":"Athanasios","family":"Anagnostis","sequence":"additional","affiliation":[]},{"given":"Konstantinos","family":"Papageorgiou","sequence":"additional","affiliation":[]},{"given":"Anna","family":"Feleki","sequence":"additional","affiliation":[]},{"given":"Dionysis","family":"Bochtis","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","article-title":"Densely Connected Convolutional Networks","author":"douillard","year":"2020","journal-title":"Densely Connected Convolutional Networks"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s13244-018-0639-9"},{"article-title":"Striving for simplicity: The all convolutional net","year":"2015","author":"springenberg","key":"ref31"},{"key":"ref30","article-title":"An Introduction to Convolutional Neural Networks","author":"o\u2019shea","year":"2015","journal-title":"ArXiv Preprint"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"journal-title":"Google colab","article-title":"Colaboratory cloud environment supported by Google","year":"0","key":"ref35"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2004.08.181"},{"key":"ref11","first-page":"287","article-title":"The detection of bone metastases in patients with highrisk prostate cancer: 99mTc-MDP Planar bone scintigraphy, singleand multi-field-of-view SPECT, 18F-fluoride PET, and 18F-fluoride PET\/CT","volume":"47","author":"even-sapir","year":"2006","journal-title":"Journal of Nuclear Medicine"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-016-3415-4"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1053\/ctrv.2000.0210"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.07.005"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"392","DOI":"10.2741\/4725","article-title":"State-of-the-art review on deep learning in medical imaging","volume":"24","author":"biswas","year":"2019","journal-title":"Frontiers in Bioscience (Landmark Edition)"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.zemedi.2018.11.002"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-019-2823-4"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.108.055061"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s12149-012-0620-5"},{"journal-title":"Classification in Bone Scintigraphy Images Using Convolutional Neural Networks","year":"2016","author":"dang","key":"ref28"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-06-0931"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"7192","DOI":"10.1038\/s41598-019-43656-y","article-title":"A convolutional neural network-based system to prevent patient misidentification in FDG-PET examinations","volume":"9","author":"kawauchi","year":"2019","journal-title":"Scientific Reports"},{"journal-title":"Bone metastases in advanced prostate cancer Management","year":"2018","author":"sartor","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2007.02.002"},{"journal-title":"Convolutional Neural Networks for Classification of Prostate Cancer Metastases Using Bone Scan Images","year":"2017","author":"belcher","key":"ref29"},{"key":"ref5","first-page":"374","article-title":"Diagnosis of bone metastasis: recent comparative studies of imaging modalities","volume":"55","author":"talbot","year":"2011","journal-title":"Q J Nucl Med Mol Imaging"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1177\/0284185114564438"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.4329\/wjr.v7.i8.202"},{"key":"ref2","article-title":"A. Management of bone metastases in cancer: a review, Crit Rev Oncol Hematol","author":"battafarano","year":"2005","journal-title":"Int J Mol Sci"},{"key":"ref9","first-page":"15","article-title":"Conventional imaging and computerized tomography in diagnosis of skeletal metastases","volume":"35","author":"rieden","year":"1995","journal-title":"Radiologe"},{"key":"ref1","first-page":"321","article-title":"Bone Metastases: An Overview","volume":"11","author":"macedo","year":"2017","journal-title":"Oncol Rev"},{"key":"ref20","article-title":"Evaluation of a revised version of computerassisted diagnosis system, BONENAVI version 2.1.7, for bone scintigraphy in cancer patients","author":"koizumi","year":"2015","journal-title":"Annals of Nuclear Medicine"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-bioeng-071516-044442"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1159\/000481227"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/9512370"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.3390\/app10030997"},{"key":"ref26","first-page":"285","article-title":"Can CNN detect the location of malignant uptake on FDG PET-CT?","volume":"60","author":"furuya","year":"2019","journal-title":"J Nucl Med"},{"key":"ref25","first-page":"1210","article-title":"A convolutional neural network-based system to detect malignant findings in FDG PET-CT examinations","volume":"60","author":"furuya","year":"2019","journal-title":"J Nucl Med"}],"event":{"name":"2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA)","start":{"date-parts":[[2020,7,15]]},"location":"Piraeus, Greece","end":{"date-parts":[[2020,7,17]]}},"container-title":["2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9284145\/9284146\/09284370.pdf?arnumber=9284370","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T17:53:35Z","timestamp":1656438815000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9284370\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,15]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/iisa50023.2020.9284370","relation":{},"subject":[],"published":{"date-parts":[[2020,7,15]]}}}