{"id":5643,"date":"2023-09-04T03:14:51","date_gmt":"2023-09-04T03:14:51","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-collection\/pancreas-ct\/"},"modified":"2023-09-13T12:01:12","modified_gmt":"2023-09-13T12:01:12","slug":"pancreas-ct","status":"publish","type":"tcia_collection","link":"https:\/\/cm.vastapps.dev\/tcia-collection\/pancreas-ct\/","title":{"rendered":"PANCREAS-CT"},"featured_media":0,"template":"","citation-tax":[],"cancer_types":["Healthy Controls (non-cancer)"],"citations":[4562,4563,2925],"collection_doi":"10.7937\/K9\/TCIA.2016.tNB1kqBU","collection_download_info":"Click the Versions tab for more info about data releases.","collection_downloads":[5161,5162],"full_export":"<div class=\"contentLayout2\">\n<div class=\"columnLayout two-right-sidebar\" data-layout=\"two-right-sidebar\">\n<div class=\"cell normal\" data-type=\"normal\">\n<div class=\"innerCell\">\n<div class=\"wiki-content\"><h2 id=\"PancreasCT-Summary\">Summary<\/h2><p>The National Institutes of Health Clinical Center performed 82 abdominal contrast enhanced 3D CT scans (~70 seconds after intravenous contrast injection in portal-venous) from 53 male and 27 female subjects.\u00a0 Seventeen of the subjects are healthy kidney donors scanned prior to nephrectomy.\u00a0 The remaining 65 patients were selected by a radiologist from patients who neither had major abdominal pathologies nor pancreatic cancer lesions.\u00a0 Subjects' ages range from 18 to 76 years with a mean age of 46.8 \u00b1 16.7. The CT scans have resolutions of 512x512 pixels with varying pixel sizes and slice thickness between 1.5 \u2212 2.5 mm, acquired on Philips and Siemens MDCT scanners (120 kVp tube voltage).<\/p><p>A medical student manually performed slice-by-slice segmentations of the pancreas as ground-truth and these were verified\/modified by an experienced radiologist.<\/p><p><br\/><\/p><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=\"#22514040c56be89073824ef7946e58d813146283\"><strong>Data Access<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#225140402b0ca4b796264b66888788d00ac1ec28\"><strong>Detailed Description<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#225140405a525c7710d147e8bfc6611f18577bb7\"><strong>Citations &amp; Data Usage Policy<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#22514040f63496e0668f4ae0b9adccc8c9833fdd\"><strong>Versions<\/strong><\/a> <\/li><\/ul><div class=\"tabs-pane  active-pane \" id=\"22514040c56be89073824ef7946e58d813146283\" active=\"true\" name=\"Data Access\" ><h3 id=\"PancreasCT-DataAccess\">Data Access<\/h3><div class=\"table-wrap\"><table class=\"wrapped relative-table confluenceTable\" style=\"width: 59.3358%;\"><colgroup><col style=\"width: 31.0112%;\"\/><col style=\"width: 36.1359%;\"\/><col style=\"width: 32.8463%;\"\/><\/colgroup><tbody><tr><th class=\"confluenceTh\">Data Type<\/th><th class=\"confluenceTh\">Download all or Query\/Filter<\/th><th class=\"confluenceTh\"><div class=\"content-wrapper\"><p>License<\/p><\/div><\/th><\/tr><tr><td class=\"confluenceTd\">Images (DICOM, 9.3 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:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/22514040\/Pancreas-CT%2020200910.tcia?version=1&amp;modificationDate=1599754273288&amp;api=v2\" 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:\/\/www.cancerimagingarchive.net\/nbia-search\/?CollectionCriteria=Pancreas-CT\" 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 requires <a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\" rel=\"nofollow\">NBIA Data Retriever<\/a>)<\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/3.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 3.0<\/a><\/p><\/div><\/td><\/tr><tr><td class=\"confluenceTd\">Manual Annotations<\/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:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/22514040\/TCIA_pancreas_labels-02-05-2017.zip?version=1&amp;modificationDate=1488846745296&amp;api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span><\/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><p>\n<h3 id=\"PancreasCT-AdditionalResourcesforthisDataset\">Additional Resources for this Dataset<\/h3>\n<p>The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.<\/p><\/p><ul><li class=\"auto-cursor-target\"><a href=\"https:\/\/portal.imaging.datacommons.cancer.gov\/explore\/filters\/?collection_id=pancreas_ct\" class=\"external-link\" rel=\"nofollow\">Imaging Data Commons (IDC)<\/a> (Imaging Data)<\/li><\/ul><\/div><div class=\"tabs-pane \" id=\"225140402b0ca4b796264b66888788d00ac1ec28\" name=\"Detailed Description\" ><h3 id=\"PancreasCT-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\"><p>Collection Statistics<\/p><\/div><\/th><th class=\"confluenceTh\"><div class=\"tablesorter-header-inner\"><p><br\/><\/p><\/div><\/th><\/tr><tr><td class=\"confluenceTd\"><p>Modalities<\/p><\/td><td class=\"confluenceTd\"><p>CT<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Participants<\/p><\/td><td class=\"confluenceTd\"><p>80<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Studies<\/p><\/td><td class=\"confluenceTd\"><p>80<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Series<\/p><\/td><td class=\"confluenceTd\"><p>80<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Images<\/p><\/td><td class=\"confluenceTd\"><p>18,942<\/p><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Image Size (GB)<\/td><td colspan=\"1\" class=\"confluenceTd\">9.3<\/td><\/tr><\/tbody><\/table><\/div><h3 id=\"PancreasCT-DataExample\">Data Example<\/h3><p><br\/><\/p><p><span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\"><img class=\"confluence-embedded-image confluence-content-image-border\" draggable=\"false\" height=\"162\" width=\"663\" src=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/embedded-page\/Public\/Pancreas-CT\/image2016-2-9%2011:48:19.png?api=v2\"><\/span><\/p><h3 class=\"TextBody\" id=\"PancreasCT-Note\"><strong>Note<\/strong><\/h3><p>The DICOM files were created from anonymized volumetric images (Analyze and NifTI) using this from ITK: <a href=\"http:\/\/www.itk.org\/Doxygen\/html\/Examples_2IO_2ImageReadDicomSeriesWrite_8cxx-example.html\" class=\"external-link\" rel=\"nofollow\"> <em>http:\/\/www.itk.org\/Doxygen\/html\/Examples_2IO_2ImageReadDicomSeriesWrite_8cxx-example.html<\/em> <\/a> <em>.<\/em><\/p><p><br\/><\/p><\/div><div class=\"tabs-pane \" id=\"225140405a525c7710d147e8bfc6611f18577bb7\" name=\"Citations BITVOODOO_ANDamp; Data Usage Policy\" ><h3 id=\"PancreasCT-Citations&amp;DataUsagePolicy\">Citations &amp; Data Usage Policy\u00a0<\/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>Roth, H., Farag, A., Turkbey, E. B., Lu, L., Liu, J., &amp; Summers, R. M. (2016). Data From Pancreas-CT (Version 2) [Data set]. The Cancer Imaging Archive. <a href=\"https:\/\/doi.org\/10.7937\/K9\/TCIA.2016.tNB1kqBU\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.7937\/K9\/TCIA.2016.tNB1kqBU<\/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>Roth HR, Lu L, Farag A, Shin H-C, Liu J, Turkbey EB, Summers RM. <strong>DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation<\/strong>. N. Navab et al. (Eds.): MICCAI 2015, Part I, LNCS 9349, pp. 556\u2013564, 2015.\u00a0 (<a href=\"https:\/\/arxiv.org\/abs\/1506.06448\" class=\"external-link\" rel=\"nofollow\">arXiv <\/a>link) <span style=\"color: rgb(51,51,51);\"><a href=\"https:\/\/doi.org\/10.1007\/978-3-319-24553-9_68\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1007\/978-3-319-24553-9_68<\/a><\/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\">https:\/\/doi.org\/10.1007\/s10278-013-9622-7<\/a><\/p><\/div><\/div><h3 id=\"PancreasCT-OtherPublicationsUsingThisData\">Other Publications Using This Data<\/h3><p><span style=\"color: rgb(33,37,41);\">TCIA maintains<\/span><span style=\"color: rgb(33,37,41);\">\u00a0<\/span><a style=\"text-decoration: none;text-align: left;\" rel=\"nofollow\" class=\"external-link\" href=\"https:\/\/www.cancerimagingarchive.net\/publications\/\">a list of publications<\/a><span style=\"color: rgb(33,37,41);\">\u00a0<\/span><span style=\"color: rgb(33,37,41);\">that leverage TCIA data.\u00a0<\/span><span style=\"color: rgb(33,37,41);\">If you have a manuscript you'd like to add please<\/span><a class=\"external-link\" rel=\"nofollow\" href=\"http:\/\/www.cancerimagingarchive.net\/support\/\" style=\"text-decoration: none;text-align: left;\"><span>\u00a0<\/span>contact the TCIA Helpdesk<\/a><span style=\"color: rgb(33,37,41);\">.<span>\u00a0<\/span><\/span><span style=\"color: rgb(33,37,41);\">Below is a list of such publications using this Collection:<\/span><\/p><ul><li>Gibson, E., Giganti, F., Hu, Y., Bonmati, E., Bandula, S., Gurusamy, K., . . . Barratt, D. C. (2017). Towards Image-Guided Pancreas and Biliary Endoscopy: Automatic Multi-organ Segmentation on Abdominal CT with Dense Dilated Networks. Paper presented at the International Conference on Medical Image Computing and Computer-Assisted Intervention.<\/li><li>Greenspan, H., van Ginneken, B., &amp; Summers, R. M. (2016). Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique. IEEE Transactions on Medical Imaging, 35(5), 1153-1159. doi:10.1109\/TMI.2016.2553401<\/li><li>Shi, H., Lu, L., Yin, M., Zhong, C., &amp; Yang, F. (2023). Joint few-shot registration and segmentation self-training of 3D medical images. Biomedical Signal Processing and Control, 80. doi:<a href=\"https:\/\/doi.org\/10.1016\/j.bspc.2022.104294\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1016\/j.bspc.2022.104294<\/a><\/li><\/ul><\/div><div class=\"tabs-pane \" id=\"22514040f63496e0668f4ae0b9adccc8c9833fdd\" name=\"Versions\" ><h3 id=\"PancreasCT-Version2(Current):Updated2020\/09\/10\">Version 2 (Current): Updated 2020\/09\/10<\/h3><div class=\"table-wrap\"><table class=\"wrapped confluenceTable\"><colgroup> <col\/> <col\/> <\/colgroup><tbody><tr><th colspan=\"1\" class=\"confluenceTh\">Data Type<\/th><th colspan=\"1\" class=\"confluenceTh\">Download all or Query\/Filter<\/th><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Images (DICOM, 9.3 GB)<\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/22514040\/Pancreas-CT%2020200910.tcia?version=1&amp;modificationDate=1599754273288&amp;api=v2\" 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:\/\/www.cancerimagingarchive.net\/nbia-search\/?CollectionCriteria=Pancreas-CT\" 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 requires\u00a0the\u00a0<a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\" rel=\"nofollow\">NBIA Data Retriever<\/a>)<\/p><\/div><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Manual Annotations<\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/22514040\/TCIA_pancreas_labels-02-05-2017.zip?version=1&amp;modificationDate=1488846745296&amp;api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><p>Note: Previously posted cases #25 and #70 were found to be from the same scan as case #2, just cropped slightly differently, and were removed from this version of the dataset.<\/p><h3 id=\"PancreasCT-Version1:Updated2015\/12\/29\">Version 1 : Updated 2015\/12\/29<\/h3><div class=\"table-wrap\"><table class=\"wrapped confluenceTable\"><colgroup> <col\/> <col\/> <\/colgroup><tbody><tr><th colspan=\"1\" class=\"confluenceTh\">Data Type<\/th><th colspan=\"1\" class=\"confluenceTh\">Download all or Query\/Filter<\/th><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Images (DICOM, 10.2 GB)<\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p>not available, see version 2<\/p><\/div><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Manual Annotations<\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/22514040\/TCIA_pancreas_labels-02-05-2017.zip?version=1&amp;modificationDate=1488846745296&amp;api=v2\" rel=\"nofollow\"><button class=\"tcia-btn tcia-download-color\"><i class=\"fa fa-cloud-download\" \/> Download<\/button><\/a>\u00a0\n<\/span><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><\/div><\/div><\/div><\/div><div class=\"localtabs-macro\"><div class=\"aui-tabs horizontal-tabs\"><div class=\"tabs-pane active-pane\"><p><br\/><\/p><\/div><\/div><\/div><\/div><\/div>\n<\/div>\n<div class=\"cell aside\" data-type=\"aside\">\n<div class=\"innerCell\">\n<p><br\/><\/p><\/div>\n<\/div>\n<\/div>\n<\/div>","versions":false,"additional_resources":"The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.\n \n<ul><li><a href=\"https:\/\/portal.imaging.datacommons.cancer.gov\/explore\/filters\/?collection_id=pancreas_ct\">Imaging Data Commons (IDC)<\/a> (Imaging Data)<\/li><\/ul>","cancer_locations":["Pancreas"],"collection_page_accessibility":"Public","publications_related":"","version_change_log":"","version_change_log_archived":"","analysis_results":"","collection_status":"Complete","publications_using":"TCIA maintains\u00a0<a href=\"https:\/\/www.cancerimagingarchive.net\/publications\/\">a list of publications<\/a>\u00a0that leverage TCIA data.\u00a0If you have a manuscript you'd like to add please<a href=\"http:\/\/www.cancerimagingarchive.net\/support\/\">\u00a0contact the TCIA Helpdesk<\/a>.\u00a0Below is a list of such publications using this Collection:\n<ul><li>Gibson, E., Giganti, F., Hu, Y., Bonmati, E., Bandula, S., Gurusamy, K., . . . Barratt, D. C. (2017). Towards Image-Guided Pancreas and Biliary Endoscopy: Automatic Multi-organ Segmentation on Abdominal CT with Dense Dilated Networks. Paper presented at the International Conference on Medical Image Computing and Computer-Assisted Intervention.<\/li><li>Greenspan, H., van Ginneken, B., &amp; Summers, R. M. (2016). Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique. IEEE Transactions on Medical Imaging, 35(5), 1153-1159. doi:10.1109\/TMI.2016.2553401<\/li><li>Shi, H., Lu, L., Yin, M., Zhong, C., &amp; Yang, F. (2023). Joint few-shot registration and segmentation self-training of 3D medical images. Biomedical Signal Processing and Control, 80. doi:<a href=\"https:\/\/doi.org\/10.1016\/j.bspc.2022.104294\">https:\/\/doi.org\/10.1016\/j.bspc.2022.104294<\/a><\/li><\/ul>","species":["Human"],"collection_title":"Pancreas-CT","detailed_description":"<h3>Data Example<\/h3>\n<br\/>\n<div class=\"cm-content-image\"><a href=\"\/wp-content\/uploads\/image2016-2-9-114819.png\" rel=\"prettyPhoto noopener\" target=\"_blank\"><img src=\"\/wp-content\/uploads\/image2016-2-9-114819.png\"\/><\/a><\/div>\n<h3><strong>Note<\/strong><\/h3>\nThe DICOM files were created from anonymized volumetric images (Analyze and NifTI) using this from ITK: <a href=\"http:\/\/www.itk.org\/Doxygen\/html\/Examples_2IO_2ImageReadDicomSeriesWrite_8cxx-example.html\"> <em>http:\/\/www.itk.org\/Doxygen\/html\/Examples_2IO_2ImageReadDicomSeriesWrite_8cxx-example.html<\/em> <\/a> <em>.<\/em>\n<br\/>","related_analysis_results":false,"subjects":"82","collection_short_title":"Pancreas-CT","data_types":["CT"],"date_updated":"2023-09-13","collection_browse_title":"","supporting_data":["Image Analyses"],"collection_featured_image":false,"collection_summary":"The National Institutes of Health Clinical Center performed 82 abdominal contrast enhanced 3D CT scans (~70 seconds after intravenous contrast injection in portal-venous) from 53 male and 27 female subjects.\u00a0 Seventeen of the subjects are healthy kidney donors scanned prior to nephrectomy.\u00a0 The remaining 65 patients were selected by a radiologist from patients who neither had major abdominal pathologies nor pancreatic cancer lesions.\u00a0 Subjects' ages range from 18 to 76 years with a mean age of 46.8 \u00b1 16.7. The CT scans have resolutions of 512x512 pixels with varying pixel sizes and slice thickness between 1.5 \u2212 2.5 mm, acquired on Philips and Siemens MDCT scanners (120 kVp tube voltage).\nA medical student manually performed slice-by-slice segmentations of the pancreas as ground-truth and these were verified\/modified by an experienced radiologist.\n<br\/>","collection_acknowledgements":"","collection_funding":"","hide_from_browse_table":[],"_links":{"self":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/collections\/5643"}],"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=5643"}],"wp:term":[{"taxonomy":"tcia_citation_tax","embeddable":true,"href":"https:\/\/cm.vastapps.dev\/api\/v1\/citation-tax?post=5643"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}