{"id":5688,"date":"2023-09-04T03:18:21","date_gmt":"2023-09-04T03:18:21","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-collection\/sn-am\/"},"modified":"2023-09-13T12:03:10","modified_gmt":"2023-09-13T12:03:10","slug":"sn-am","status":"publish","type":"tcia_collection","link":"https:\/\/cm.vastapps.dev\/tcia-collection\/sn-am\/","title":{"rendered":"SN-AM"},"featured_media":0,"template":"","citation-tax":[],"cancer_types":["Leukemia","Multiple Myeloma"],"citations":[4632,4633,4634,2925],"collection_doi":"10.7937\/tcia.2019.of2w8lxr","collection_download_info":"Click the\u00a0 <strong>Download<\/strong>  button\u00a0to browse and download the data from Box.\n\nClick the Versions tab for more info about data releases.","collection_downloads":[5265],"full_export":"<h2 id=\"SNAMDataset:WhiteBloodcancerdatasetofBALLandMMforstainnormalization(SNAM)-Summary\">Summary<\/h2><div class=\"wiki-content\"><span>Microscopic images were captured from bone marrow aspirate slides of patients diagnosed with B-lineage Acute Lymphoid Leukemia (B-ALL) and Multiple Myeloma (MM) as per the standard guidelines. Slides were stained using Jenner-Giemsa stain. Images were captured at 1000x magnification using Nikon Eclipse-200 microscope equipped with a digital camera. Images were captured in raw BMP format with a size of 2560x1920 pixels. In all, this dataset consists of 90 images of B-ALL and 100 images of MM. Both MM and B-ALL images have sufficient variability from one image to another image to rigorously test any stain normalization methodology developed.\u00a0 More information about each subset are provided on the Detailed Description tab below.<\/span><h4 class=\"auto-cursor-target\" id=\"SNAMDataset:WhiteBloodcancerdatasetofBALLandMMforstainnormalization(SNAM)-AdditionalPublicationsusingthisdataset:\"><strong>Additional Publications using this dataset:<\/strong><\/h4><ul><li>Ritu Gupta, Pramit Mallick, Rahul Duggal, Anubha Gupta, and Ojaswa Sharma, &quot;Stain Color Normalization and Segmentation of Plasma Cells in Microscopic Images as a Prelude to Development of Computer Assisted Automated Disease Diagnostic Tool in Multiple Myeloma,&quot; 16th International Myeloma Workshop (IMW), India, March 2017.<\/li><li>Rahul Duggal, Anubha Gupta, Ritu Gupta, and Pramit Mallick, &quot;SD-Layer: Stain Deconvolutional Layer for CNNs in Medical Microscopic Imaging,&quot; In: Descoteaux M., Maier- Hein L., Franz A., Jannin P., Collins D., Duchesne S. (eds) Medical Image Computing and Computer-Assisted Intervention \u2212 MICCAI 2017, MICCAI 2017. Lecture Notes in Computer Science, Part III, LNCS 10435, pp. 435\u2013443. Springer, Cham. DOI: <a href=\"https:\/\/doi.org\/10.1007\/978-3-319-66179-7_50\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1007\/978-3-319-66179-7_50<\/a> .<\/li><li>Rahul Duggal, Anubha Gupta, Ritu Gupta, Manya Wadhwa, and Chirag Ahuja, \u201cOverlapping Cell Nuclei Segmentation in Microscopic Images UsingDeep Belief Networks,\u201d Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), India, December 2016.<\/li><\/ul><\/div><div class=\"wiki-content\"><div class=\"tab-style-builtin\"><div class=\"localtabs-macro\"><div class=\"aui-tabs horizontal-tabs\" role=\"application\" data-aui-responsive=\"true\"><ul class=\"tabs-menu\"><li class=\"menu-item bv-localtab  active-tab \"><a href=\"#527570092940c0a84c0a4a31bbd62942f9a23520\"><strong>Data Access<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#527570098e6d7a326d3c4b6ab006ace47c50f7fc\"><strong>Detailed Description<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#5275700958e4ca4e2d624cf89967e529d4b92996\"><strong>Citations &amp; Data Usage Policy<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#52757009180a250d2c424529aaa017b5db7f1a37\"><strong>Versions<\/strong><\/a> <\/li><\/ul><div class=\"tabs-pane  active-pane \" id=\"527570092940c0a84c0a4a31bbd62942f9a23520\" active=\"true\" name=\"Data Access\" ><h3 id=\"SNAMDataset:WhiteBloodcancerdatasetofBALLandMMforstainnormalization(SNAM)-DataAccess\">Data Access<\/h3><p><span>Click the\u00a0<\/span> <strong>Download<\/strong> <span> button\u00a0to browse and download the data from Box.<\/span><\/p><div class=\"table-wrap\"><table class=\"wrapped relative-table confluenceTable\" style=\"width: 90.8725%;\"><colgroup><col style=\"width: 29.497%;\"\/><col style=\"width: 38.8483%;\"\/><col style=\"width: 31.6447%;\"\/><\/colgroup><tbody><tr><th class=\"confluenceTh\">Data Type<\/th><th class=\"confluenceTh\">Download all or Query\/Filter<\/th><th class=\"confluenceTh\">License<\/th><\/tr><tr><td class=\"confluenceTd\">Images (BMP, 2.9 GB)<\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/faspex.cancerimagingarchive.net\/aspera\/faspex\/external_deliveries\/73?passcode=9b10a5486bb8ca48a0df18a517b745445aa8706f\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span><span class=\"confluence-link\">\u00a0<\/span>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/pathdb.cancerimagingarchive.net\/imagesearch?f[0]=collection:sn_am\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-search-color\"><i class=\"fa fa-search\" \/> Search<\/button><\/a>\u00a0\n<\/span><br\/><\/p><p>(Download and apply the\u00a0<a href=\"https:\/\/www.ibm.com\/aspera\/connect\/\" class=\"external-link\" rel=\"nofollow\">IBM-Aspera-Connect plugin\u00a0<\/a>to your browser to retrieve this faspex package)\u00a0<\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p><span class=\"confluence-link\">\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/3.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 3.0<\/a><br\/><\/span><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><p>Click the Versions tab for more info about data releases.<\/p><\/div><div class=\"tabs-pane \" id=\"527570098e6d7a326d3c4b6ab006ace47c50f7fc\" name=\"Detailed Description\" ><h3 id=\"SNAMDataset:WhiteBloodcancerdatasetofBALLandMMforstainnormalization(SNAM)-DetailedDescription\">Detailed Description<\/h3><div class=\"table-wrap\"><table class=\"wrapped confluenceTable\"><colgroup> <col\/> <col\/> <\/colgroup><tbody><tr><th class=\"confluenceTh\"><div class=\"tablesorter-header-inner\"><div class=\"tablesorter-header-inner\"><p>Image Statistics<\/p><\/div><\/div><\/th><th class=\"confluenceTh\"><div class=\"tablesorter-header-inner\"><div class=\"tablesorter-header-inner\"><p><br\/><\/p><\/div><\/div><\/th><\/tr><tr><td class=\"confluenceTd\"><p>Modalities<\/p><\/td><td class=\"confluenceTd\"><p>Pathology<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Participants<\/p><\/td><td class=\"confluenceTd\"><p>16<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Studies<\/p><\/td><td class=\"confluenceTd\"><p>60<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Images<\/p><\/td><td class=\"confluenceTd\"><p>190<\/p><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Images Size (GB)<\/td><td colspan=\"1\" class=\"confluenceTd\">2.9<\/td><\/tr><\/tbody><\/table><\/div><p><strong>Data subset-1: ALL images<\/strong><\/p><p>Microscopic images were captured from bone marrow aspirate slides of patients diagnosed with B-lineage Acute Lymphoblastic Leukemia (B-ALL). Slides were stained using Jenner-Giemsa stain and lymphoblasts, that are cells of interest, have been evaluated. Images were captured in raw BMP format with a size of 2560x1920 pixels using Nikon Eclipse-200 microscope equipped with a digital camera at 1000x magnification. In all, this dataset consists of 30 images, wherein one image has been used as the reference image and the proposed stain normalization method has been tested on 29 images. For each of these 30 images, we have also provided two additional images that contain the nucleus mask and the background mask, respectively, for that particular image. For example, if the original file is saved with the name \u201cALL_1.bmp\u201d, the corresponding image with mask on the nuclei is saved as \u201cALL_1_nucleus_mask.bmp\u201d, and the corresponding image with mask on the background is saved as \u201cALL_1_background_mask.bmp Thus, in all, we have 90 images for this dataset.<\/p><p><strong>Data subset-2: MM images<\/strong><\/p><p>The third data subset contains microscopic images captured from slides prepared from bone marrow aspirate collected from patients with Multiple Myeloma (MM). Slides are stained using Jenner-Giemsa stain and plasma cells, that are cells of interest, have been evaluated. A total of 30 images have been considered, wherein one image has been used as the reference image to which 29 images have been stain normalized. For each of these 30 images, we have also provided two additional images that contain the nucleus mask and the background mask, respectively, for that particular image. For example, if the original file is saved with the name \u201cMM_1.bmp\u201d, the corresponding image with mask on the nuclei is saved as \u201cMM_1_nucleus_mask.bmp\u201d, and the corresponding image with mask on the background is saved as \u201cMM_1_background_mask.bmp. In addition, for 17 images, the mask images are also provided for the cytoplasm of the plasma cells, namely, \u201cMM_1_cyto_mask.bmp. Thus, in all, we have 100 images for this dataset.<\/p><\/div><div class=\"tabs-pane \" id=\"5275700958e4ca4e2d624cf89967e529d4b92996\" name=\"Citations BITVOODOO_ANDamp; Data Usage Policy\" ><h3 id=\"SNAMDataset:WhiteBloodcancerdatasetofBALLandMMforstainnormalization(SNAM)-Citations&amp;DataUsagePolicy\">Citations &amp; Data Usage Policy<\/h3><p class=\"auto-cursor-target\">\n<p>\nUsers must abide by the <a href=\"https:\/\/wiki.cancerimagingarchive.net\/x\/c4hF\" class=\"external-link\" rel=\"nofollow\">TCIA Data Usage Policy and Restrictions<\/a>. Attribution should include references to the following citations:\n<\/p><\/p><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Data Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p><span style=\"color: rgb(51,51,51);text-decoration: none;\">Gupta, A., &amp; Gupta, R. (2019). <strong>SN-AM Dataset: White Blood Cancer Dataset of B-ALL and MM for Stain Normalization [Data set]<\/strong>. The Cancer Imaging Archive. <a href=\"https:\/\/doi.org\/10.7937\/tcia.2019.of2w8lxr\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.7937\/tcia.2019.of2w8lxr<\/a><\/span><\/p><\/div><\/div><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Publication Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p>Anubha Gupta, Rahul Duggal, Shiv Gehlot, Ritu Gupta, Anvit Mangal, Lalit Kumar, Nisarg Thakkar, and Devprakash Satpathy, &quot;GCTI-SN: Geometry-Inspired Chemical and Tissue Invariant Stain Normalization of Microscopic Medical Images,&quot; Medical Image Analysis, vol. 65, Oct 2020. DOI:\u00a0<a href=\"https:\/\/urldefense.proofpoint.com\/v2\/url?u=https-3A__doi.org_10.1016_j.media.2020.101788&amp;d=DwMGaQ&amp;c=27AKQ-AFTMvLXtgZ7shZqsfSXu-Fwzpqk4BoASshREk&amp;r=8Cp6b3lxarmeusUZiM4iklR8j0cnPVpMQlwxcUdmg7k&amp;m=Jg1DYoflJFZLyRcI0f0eYIx1CjF5Fi6EE1AoUEp0WxU&amp;s=pKszA6mKSkGqcdE2O8Q6gW6jA23ur9RN8nXVZauH-WE&amp;e=\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1016\/j.media.2020.101788<\/a>.<\/p><\/div><\/div><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">Publication Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p><span style=\"letter-spacing: 0.0px;\">Anubha Gupta, Pramit Mallick, Ojaswa Sharma, Ritu Gupta, and Rahul Duggal, &quot;PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma,&quot; PLoS ONE 13(12): e0207908, Dec 2018, DOI: <\/span><a style=\"letter-spacing: 0.0px;\" href=\"https:\/\/urldefense.proofpoint.com\/v2\/url?u=https-3A__doi.org_10.1371_journal.pone.0207908&amp;d=DwMGaQ&amp;c=27AKQ-AFTMvLXtgZ7shZqsfSXu-Fwzpqk4BoASshREk&amp;r=8Cp6b3lxarmeusUZiM4iklR8j0cnPVpMQlwxcUdmg7k&amp;m=Jg1DYoflJFZLyRcI0f0eYIx1CjF5Fi6EE1AoUEp0WxU&amp;s=O123oXofJO-PT6nsVKeychevebx5toOcgyJ2ZNAwjKg&amp;e=\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1371\/journal.pone.0207908<\/a><span style=\"letter-spacing: 0.0px;\">.<\/span><\/p><\/div><\/div><div class=\"confluence-information-macro confluence-information-macro-information\"><p class=\"title\">TCIA Citation<\/p><span class=\"aui-icon aui-icon-small aui-iconfont-info confluence-information-macro-icon\"><\/span><div class=\"confluence-information-macro-body\"><p>Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F.\u00a0<strong>The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository<\/strong>, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: <a href=\"https:\/\/doi.org\/10.1007\/s10278-013-9622-7\" class=\"external-link\" rel=\"nofollow\">10.1007\/s10278-013-9622-7<\/a><\/p><\/div><\/div><h3 id=\"SNAMDataset:WhiteBloodcancerdatasetofBALLandMMforstainnormalization(SNAM)-OtherPublicationsUsingThisData\">Other Publications Using This Data<\/h3><p><span>TCIA maintains<\/span> <a href=\"https:\/\/www.cancerimagingarchive.net\/publications\/\" class=\"external-link\" rel=\"nofollow\"> a list of publications<\/a> <span> which leverage TCIA data. <\/span> If you have a manuscript you'd like to add please<a href=\"http:\/\/www.cancerimagingarchive.net\/support\/\" class=\"external-link\" rel=\"nofollow\"> contact the TCIA Helpdesk<\/a>.<\/p><\/div><div class=\"tabs-pane \" id=\"52757009180a250d2c424529aaa017b5db7f1a37\" name=\"Versions\" ><h3 id=\"SNAMDataset:WhiteBloodcancerdatasetofBALLandMMforstainnormalization(SNAM)-Version1(Current):Updated2019\/03\/26\">Version 1 (Current): Updated 2019\/03\/26<\/h3><div class=\"table-wrap\"><table class=\"wrapped relative-table confluenceTable\" style=\"width: 63.8521%;\"><colgroup> <col style=\"width: 36.753%;\"\/> <col style=\"width: 63.2409%;\"\/> <\/colgroup><tbody><tr><th class=\"confluenceTh\"><span>Data Type<\/span><\/th><th class=\"confluenceTh\"><span>Download all or Query\/Filter<\/span><\/th><\/tr><tr><td class=\"confluenceTd\"><span>Images (BMP, 2.9 GB)<br\/><\/span><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/faspex.cancerimagingarchive.net\/aspera\/faspex\/external_deliveries\/73?passcode=9b10a5486bb8ca48a0df18a517b745445aa8706f\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/pathdb.cancerimagingarchive.net\/imagesearch?f[0]=collection:sn_am\" class=\"external-link\" rel=\"nofollow\"><button class=\"tcia-btn tcia-search-color\"><i class=\"fa fa-search\" \/> Search<\/button><\/a>\u00a0\n<\/span><br\/><\/p><p>(Download and apply the\u00a0<a href=\"https:\/\/www.ibm.com\/aspera\/connect\/\" class=\"external-link\" rel=\"nofollow\">IBM-Aspera-Connect plugin\u00a0<\/a>to your browser to retrieve this faspex package)\u00a0<\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><p><span> <br\/><\/span><\/p><\/div><\/div><\/div><\/div><\/div><p><br\/><\/p><p><br\/><\/p><p><br\/><\/p><p><br\/><\/p><p><br\/><\/p>","versions":false,"additional_resources":"","cancer_locations":["Blood","Bone"],"collection_page_accessibility":"Public","publications_related":"","version_change_log":"","version_change_log_archived":"","analysis_results":"","collection_status":"Complete","publications_using":"<ul><li>Ritu Gupta, Pramit Mallick, Rahul Duggal, Anubha Gupta, and Ojaswa Sharma, \"Stain Color Normalization and Segmentation of Plasma Cells in Microscopic Images as a Prelude to Development of Computer Assisted Automated Disease Diagnostic Tool in Multiple Myeloma,\" 16th International Myeloma Workshop (IMW), India, March 2017.<\/li><li>Rahul Duggal, Anubha Gupta, Ritu Gupta, and Pramit Mallick, \"SD-Layer: Stain Deconvolutional Layer for CNNs in Medical Microscopic Imaging,\" In: Descoteaux M., Maier- Hein L., Franz A., Jannin P., Collins D., Duchesne S. (eds) Medical Image Computing and Computer-Assisted Intervention \u2212 MICCAI 2017, MICCAI 2017. Lecture Notes in Computer Science, Part III, LNCS 10435, pp. 435\u2013443. Springer, Cham. DOI: <a href=\"https:\/\/doi.org\/10.1007\/978-3-319-66179-7_50\">https:\/\/doi.org\/10.1007\/978-3-319-66179-7_50<\/a> .<\/li><li>Rahul Duggal, Anubha Gupta, Ritu Gupta, Manya Wadhwa, and Chirag Ahuja, \u201cOverlapping Cell Nuclei Segmentation in Microscopic Images UsingDeep Belief Networks,\u201d Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), India, December 2016.<\/li><\/ul>","species":["Human"],"collection_title":"SN-AM Dataset: White Blood cancer dataset of B-ALL and MM for stain normalization","detailed_description":"<strong>Data subset-1: ALL images<\/strong>\nMicroscopic images were captured from bone marrow aspirate slides of patients diagnosed with B-lineage Acute Lymphoblastic Leukemia (B-ALL). Slides were stained using Jenner-Giemsa stain and lymphoblasts, that are cells of interest, have been evaluated. Images were captured in raw BMP format with a size of 2560x1920 pixels using Nikon Eclipse-200 microscope equipped with a digital camera at 1000x magnification. In all, this dataset consists of 30 images, wherein one image has been used as the reference image and the proposed stain normalization method has been tested on 29 images. For each of these 30 images, we have also provided two additional images that contain the nucleus mask and the background mask, respectively, for that particular image. For example, if the original file is saved with the name \u201cALL_1.bmp\u201d, the corresponding image with mask on the nuclei is saved as \u201cALL_1_nucleus_mask.bmp\u201d, and the corresponding image with mask on the background is saved as \u201cALL_1_background_mask.bmp Thus, in all, we have 90 images for this dataset.\n<strong>Data subset-2: MM images<\/strong>\nThe third data subset contains microscopic images captured from slides prepared from bone marrow aspirate collected from patients with Multiple Myeloma (MM). Slides are stained using Jenner-Giemsa stain and plasma cells, that are cells of interest, have been evaluated. A total of 30 images have been considered, wherein one image has been used as the reference image to which 29 images have been stain normalized. For each of these 30 images, we have also provided two additional images that contain the nucleus mask and the background mask, respectively, for that particular image. For example, if the original file is saved with the name \u201cMM_1.bmp\u201d, the corresponding image with mask on the nuclei is saved as \u201cMM_1_nucleus_mask.bmp\u201d, and the corresponding image with mask on the background is saved as \u201cMM_1_background_mask.bmp. In addition, for 17 images, the mask images are also provided for the cytoplasm of the plasma cells, namely, \u201cMM_1_cyto_mask.bmp. Thus, in all, we have 100 images for this dataset.","related_analysis_results":false,"subjects":"60","collection_short_title":"SN-AM","data_types":["Pathology"],"date_updated":"2023-09-13","collection_browse_title":"","supporting_data":false,"collection_featured_image":false,"collection_summary":"Microscopic images were captured from bone marrow aspirate slides of patients diagnosed with B-lineage Acute Lymphoid Leukemia (B-ALL) and Multiple Myeloma (MM) as per the standard guidelines. Slides were stained using Jenner-Giemsa stain. Images were captured at 1000x magnification using Nikon Eclipse-200 microscope equipped with a digital camera. Images were captured in raw BMP format with a size of 2560x1920 pixels. In all, this dataset consists of 90 images of B-ALL and 100 images of MM. Both MM and B-ALL images have sufficient variability from one image to another image to rigorously test any stain normalization methodology developed.\u00a0 More information about each subset are provided on the Detailed Description tab below.","collection_acknowledgements":"","collection_funding":"","hide_from_browse_table":[],"_links":{"self":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/collections\/5688"}],"collection":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/collections"}],"about":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/types\/tcia_collection"}],"wp:attachment":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/media?parent=5688"}],"wp:term":[{"taxonomy":"tcia_citation_tax","embeddable":true,"href":"https:\/\/cm.vastapps.dev\/api\/v1\/citation-tax?post=5688"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}