{"id":41119,"date":"2023-11-20T00:41:56","date_gmt":"2023-11-20T06:41:56","guid":{"rendered":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/pca_bx_3dpathology-pub\/"},"modified":"2023-11-20T00:41:56","modified_gmt":"2023-11-20T06:41:56","slug":"pca_bx_3dpathology-pub","status":"publish","type":"tcia_citation","link":"https:\/\/stage.cancerimagingarchive.net\/tcia-citation\/pca_bx_3dpathology-pub\/","title":{"rendered":"PCA_BX_3DPATHOLOGY-PUB"},"template":"","class_list":["post-41119","tcia_citation","type-tcia_citation","status-publish"],"tcia_citation_type":"Publication Citation","tcia_citation_text":"<p><span>Xie, W., Reder, N. P., Koyuncu, C., Leo, P., Hawley, S., Huang, H., Mao, C., Postupna, N., Kang, S., Serafin, R., Gao, G., Han, Q., Bishop, K. W., Barner, L. A., Fu, P., Wright, J. L., Keene, C. D., Vaughan, J. C., Janowczyk, A., \u2026 Liu, J. T. C. (2021). Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning\u2013Assisted Gland Analysis. In Cancer Research (Vol. 82, Issue 2, pp. 334\u2013345). American Association for Cancer Research (AACR).<span>\u00a0<\/span><\/span><a href=\"https:\/\/doi.org\/10.1158\/0008-5472.can-21-2843\">https:\/\/doi.org\/10.1158\/0008-5472.can-21-2843<\/a><\/p>\n","tcia_citation_statement":"","tcia_citation_doi":"10.1158\/0008-5472.can-21-2843","_links":{"self":[{"href":"https:\/\/stage.cancerimagingarchive.net\/api\/v1\/citations\/41119","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=41119"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}