{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:24:18Z","timestamp":1742945058611,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":16,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811610851"},{"type":"electronic","value":"9789811610868"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-981-16-1086-8_5","type":"book-chapter","created":{"date-parts":[[2021,3,25]],"date-time":"2021-03-25T22:48:05Z","timestamp":1616712485000},"page":"44-55","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Radial Cumulative Frequency Distribution: A New Imaging Signature to Detect Chromosomal Arms 1p\/19q Co-deletion Status in Glioma"],"prefix":"10.1007","author":[{"given":"Debanjali","family":"Bhattacharya","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neelam","family":"Sinha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jitender","family":"Saini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,3,26]]},"reference":[{"issue":"6","key":"5_CR1","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1007\/s00401-016-1545-1","volume":"131","author":"DN Louis","year":"2016","unstructured":"Louis, D.N., et al.: The 2016 world health organization classification of tumors of the central nervous system: a summary. Acta Neuropathologica 131(6), 803\u2013820 (2016). https:\/\/doi.org\/10.1007\/s00401-016-1545-1","journal-title":"Acta Neuropathologica"},{"key":"5_CR2","doi-asserted-by":"publisher","unstructured":"Erickson, B., Akkus, Z., et al.: Data from LGG-1p19qDeletion. Cancer Imaging Arch. (2017). https:\/\/doi.org\/10.7937\/K9\/TCIA.2017.dwehtz9v","DOI":"10.7937\/K9\/TCIA.2017.dwehtz9v"},{"key":"5_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/978-3-030-40124-5_7","volume-title":"Radiomics and Radiogenomics in Neuro-oncology","author":"S Rathore","year":"2020","unstructured":"Rathore, S., Chaddad, A., Bukhari, N.H., Niazi, T.: Imaging signature of 1p\/19q co-deletion status derived via machine learning in lower grade glioma. In: Mohy-ud-Din, H., Rathore, S. (eds.) RNO-AI 2019. LNCS, vol. 11991, pp. 61\u201369. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-40124-5_7"},{"issue":"7","key":"5_CR4","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1097\/01.pas.0000213250.44822.2e","volume":"30","author":"D Scheie","year":"2006","unstructured":"Scheie, D., Andresen, P.A., et al.: Fluorescence in situ hybridization (FISH) on touch preparations: a reliable method for detecting loss of heterozygosity at 1p and 19q in oligodendroglial tumors. Am. J. Surg. Pathol. 30(7), 828\u201337 (2006)","journal-title":"Am. J. Surg. Pathol."},{"issue":"5","key":"5_CR5","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1007\/s00234-019-02173-5","volume":"61","author":"A Latysheva","year":"2019","unstructured":"Latysheva, A., et al.: Dynamic susceptibility contrast and diffusion MR imaging identify oligodendroglioma as defined by the 2016 WHO classification for brain tumors: histogram analysis approach. Neuroradiology 61(5), 545\u2013555 (2019). https:\/\/doi.org\/10.1007\/s00234-019-02173-5","journal-title":"Neuroradiology"},{"issue":"3","key":"5_CR6","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1097\/RLU.0000000000002398","volume":"44","author":"S Kebir","year":"2019","unstructured":"Kebir, S., Weber, M., et al.: Hybrid 11C-MET PET\/MRI Combined with \u201cmachine learning\u201d in glioma diagnosis according to the revised glioma WHO classification 2016. Clinical Nuclear Medicine 44(3), 214\u2013220 (2019)","journal-title":"Clinical Nuclear Medicine"},{"issue":"7","key":"5_CR7","doi-asserted-by":"publisher","first-page":"1326","DOI":"10.3174\/ajnr.A3352","volume":"34","author":"SD Fellah","year":"2013","unstructured":"Fellah, S.D., Caudal, A.M., et al.: Multimodal MR imaging (diffusion, perfusion, and spectroscopy): is it possible to distinguish oligodendroglial tumor grade and 1p\/19q codeletion in the pretherapeutic diagnosis? AJNR Am. J. Neuroradiol. 34(7), 1326\u20131333 (2013)","journal-title":"AJNR Am. J. Neuroradiol."},{"issue":"8","key":"5_CR8","doi-asserted-by":"publisher","first-page":"2357","DOI":"10.1158\/1078-0432.CCR-07-1964","volume":"14","author":"R Brown","year":"2008","unstructured":"Brown, R., Zlatescu, M., et al.: The use of magnetic resonance imaging to noninvasively detect genetic signatures in oligodendroglioma. Clin. Cancer Res. 14(8), 2357\u20132362 (2008)","journal-title":"Clin. Cancer Res."},{"issue":"12","key":"5_CR9","doi-asserted-by":"publisher","first-page":"1473","DOI":"10.1093\/neuonc\/nos259","volume":"14","author":"NL Jansen","year":"2012","unstructured":"Jansen, N.L., Schwartz, C., et al.: Prediction of oligodendroglial histology and LOH 1p\/19q using dynamic FET-PET imaging in intracranial WHO grade II and III gliomas. Neuro Oncol. 14(12), 1473\u201380 (2012)","journal-title":"Neuro Oncol."},{"issue":"4","key":"5_CR10","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1007\/s10278-017-9984-3","volume":"30","author":"Z Akkus","year":"2017","unstructured":"Akkus, Z., Ali, I., et al.: Predicting deletion of chromosomal arms 1p\/19q in low-grade gliomas from MR images using machine intelligence. J. Digit. Imaging 30(4), 469\u2013476 (2017)","journal-title":"J. Digit. Imaging"},{"issue":"9","key":"5_CR11","doi-asserted-by":"publisher","first-page":"1016","DOI":"10.1136\/jnnp-2015-311516","volume":"87","author":"Y Iwadate","year":"2016","unstructured":"Iwadate, Y., Shinozaki, N., et al.: Molecular imaging of 1p\/19q deletion in oligodendroglial tumours with 11C-methionine positron emission tomography. J. Neurol. Neurosurg. Psychiatry 87(9), 1016\u201321 (2016)","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Bhattacharya, D., Sinha, N., Saini, J.: Detection of chromosomal arms 1p\/19q codeletion in low graded glioma using probability distribution of MRI volume heterogeneity. In: Proceedings of IEEE Region 10 Conference- TENCON-2019, pp: 2695\u20132699 (2019)","DOI":"10.1109\/TENCON.2019.8929255"},{"issue":"2","key":"5_CR13","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1007\/s11060-018-2953-y","volume":"140","author":"Y Han","year":"2018","unstructured":"Han, Y., et al.: Non-invasive genotype prediction of chromosome 1p\/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas. J. Neuro-Oncol. 140(2), 297\u2013306 (2018). https:\/\/doi.org\/10.1007\/s11060-018-2953-y","journal-title":"J. Neuro-Oncol."},{"issue":"6","key":"5_CR14","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1093\/neuonc\/now256","volume":"19","author":"H Zhou","year":"2017","unstructured":"Zhou, H., Vallieres, M., et al.: MRI features predict survival and molecular markers in diffuse lower-grade gliomas. Neuro Oncol. 19(6), 862\u2013870 (2017)","journal-title":"Neuro Oncol."},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Seiffert, C., Khoshgoftaar, T.M.: RUSBoost: a hybrid approach to alleviating class imbalance. IEEE Trans. Syst. Man Cybern. - Part A: Syst. Hum. 40 (2010)","DOI":"10.1109\/TSMCA.2009.2029559"},{"key":"5_CR16","doi-asserted-by":"publisher","first-page":"e0175979","DOI":"10.1371\/journal.pone.0175979","volume":"12","author":"S Sharma","year":"2017","unstructured":"Sharma, S., Zhang, Y.: Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: a multiple sclerosis study. PLOS One 12, e0175979 (2017)","journal-title":"PLOS One"}],"container-title":["Communications in Computer and Information Science","Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-1086-8_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T20:12:55Z","timestamp":1619295175000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-1086-8_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9789811610851","9789811610868"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-1086-8_5","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"26 March 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Vision and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Prayagraj","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvip2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cvip2020.iiita.ac.in","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"352","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"134","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"38% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic the conference was partially held in a virtual mode.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}