{"id":43527,"date":"2023-11-20T03:35:57","date_gmt":"2023-11-20T09:35:57","guid":{"rendered":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/meningioma-seg-class-pub\/"},"modified":"2024-10-30T20:38:52","modified_gmt":"2024-10-31T01:38:52","slug":"meningioma-seg-class-pub","status":"publish","type":"tcia_citation","link":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/meningioma-seg-class-pub\/","title":{"rendered":"MENINGIOMA-SEG-CLASS-PUB"},"template":"","class_list":["post-43527","tcia_citation","type-tcia_citation","status-publish"],"tcia_citation_type":"Publication Citation","tcia_citation_text":"<p>Vassantachart, A., Cao, Y., Gribble, M., Guzman, S., Ye, J. C., Hurth, K., Mathew, A., Zada, G., Fan, Z., Chang, E. L., &amp; Yang, W. (2022). <strong>Automatic differentiation of Grade I and II meningiomas on magnetic resonance image using an asymmetric convolutional neural network<\/strong>. In Scientific Reports (Vol. 12, Issue 1). Springer Science and Business Media LLC. <a href=\"https:\/\/doi.org\/10.1038\/s41598-022-07859-0\">https:\/\/doi.org\/10.1038\/s41598-022-07859-0<\/a><\/p>\n","tcia_citation_statement":"","tcia_citation_doi":"10.1038\/s41598-022-07859-0","_links":{"self":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/citations\/43527","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/citations"}],"about":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/types\/tcia_citation"}],"wp:attachment":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/wp\/v2\/media?parent=43527"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}