{"id":5718,"date":"2023-09-04T03:20:56","date_gmt":"2023-09-04T03:20:56","guid":{"rendered":"https:\/\/cm.vastapps.dev\/tcia-collection\/cmmd\/"},"modified":"2023-09-13T12:04:41","modified_gmt":"2023-09-13T12:04:41","slug":"cmmd","status":"publish","type":"tcia_collection","link":"https:\/\/cm.vastapps.dev\/tcia-collection\/cmmd\/","title":{"rendered":"CMMD"},"featured_media":8433,"template":"","citation-tax":[],"cancer_types":["Breast Cancer"],"citations":[4693,4694,4695,2925],"collection_doi":"10.7937\/tcia.eqde-4b16","collection_download_info":"Click the Versions tab for more info about data releases.\nPlease contact <a href=\"mailto:help@cancerimagingarchive.net\">help@cancerimagingarchive.net<\/a>\u00a0 with any questions regarding usage.","collection_downloads":[5306,5307],"full_export":"<h1 id=\"TheChineseMammographyDatabase(CMMD)-Summary\">Summary<\/h1><p><span class=\"confluence-embedded-file-wrapper image-right-wrapper confluence-embedded-manual-size\"><img class=\"confluence-embedded-image image-right\" draggable=\"false\" height=\"250\" src=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/embedded-page\/Public\/The%20Chinese%20Mammography%20Database%20(CMMD)\/Inclusion_exclusion_criteria.png?api=v2\"><\/span><\/p><p style=\"text-align: left;\"><span style=\"color: rgb(32,33,36);\">Breast carcinoma is the second largest cancer in the world among women. Early detection of breast cancer has been shown to increase the survival rate, thereby significantly increasing patients' lifespans. Mammography, a noninvasive imaging tool with low cost, is widely used to diagnose breast disease at an early stage due to its high sensitivity. The recent popularization of artificial intelligence in computer-aided diagnosis creates opportunities for advances in areas such as\u00a0(1) Computer-aided detection for locating suspect lesions such as mass and microcalcification, leaving the classification to the radiologist; and (2) Computer-aided diagnosis for characterizing the suspicious region of lesion and\/or estimate its probability of onset; and (3) Findings of predictive image-based biomarkers by applying the computational methods to mine the potential relationships between image representation and molecular subtype, including luminal A, luminal B, HER2 positive, and Triple-negative.<\/span><\/p><p style=\"text-align: left;\"><span style=\"color: rgb(32,33,36);\">However, existing publicly available mammography databases are limited by small sample size, lack of diversity in patient populations, missing biopsy confirmations and unknown molecular sub-types.\u00a0\u00a0<\/span><span style=\"color: rgb(32,33,36);\">To help fill the gap, we built a database<span>\u00a0<\/span><\/span><span style=\"color: rgb(33,37,41);\">conducted on 1,775 patients from China with benign or malignant breast disease who underwent mammography examination between July 2012 and January 2016<\/span><span style=\"color: rgb(32,33,36);\">. The database consists of 3,728 mammographies from these 1,775 patients, with biopsy confirmed type of benign or malignant tumors. For 749 of these patients (<\/span><span style=\"color: rgb(32,33,36);\">1,498 mammographies) we also include patients' molecular subtypes. I<span style=\"color: rgb(33,37,41);\">mage\u00a0data were acquired on a GE Senographe DS mammography system.\u00a0\u00a0<\/span><\/span><\/p><p><br\/><\/p><h3 id=\"TheChineseMammographyDatabase(CMMD)-Acknowledgements\"><span>Acknowledgements<\/span><\/h3><ul><li><span style=\"color: rgb(32,33,36);\">The authors of this dataset thank the volunteers from the <strong>School of Computer Science and Engineering, South China University of Technology<\/strong> for assisting to tidy the clinical and imaging data. This work was supported by the grant from the National Natural Science Foundation of China (no.61771007).<\/span><\/li><li><span style=\"color: rgb(32,33,36);\">This work was partially supported by the <strong>Key-Area Research and Development of Guangdong Province<\/strong> under Grant (2020B010166002, 2020B1111190001), the <strong>National Natural Science Foundation of China<\/strong> (61472145, 61771007), <strong>Guangdong Natural Science Foundation<\/strong> (2017A030312008), and the <strong>Health &amp; Medical Collaborative Innovation Project of Guangzhou City<\/strong> (201803010021, 202002020049).<\/span><\/li><li>Harmonization of the components of this dataset, including into standard DICOM representation, was supported in part by the NCI Imaging Data Commons consortium. NCI Imaging Data Commons consortium is supported by the contract number 19X037Q from Leidos Biomedical Research under Task Order HHSN26100071 from NCI.<br\/><br\/><\/li><\/ul><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=\"#702305083240e43d037c47eba3f5325d0a08c9ac\"><strong>Data Access<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#7023050875edb2c998324525a079f302716bd7c4\"><strong>Detailed Description<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#70230508eafc83b6ab624b80900e0f069203bacd\"><strong>Citations &amp; Data Usage Policy<\/strong><\/a> <\/li><li class=\"menu-item bv-localtab \"><a href=\"#70230508bd92cac178f64248a9af983b338f7743\"><strong>Versions<\/strong><\/a> <\/li><\/ul><div class=\"tabs-pane  active-pane \" id=\"702305083240e43d037c47eba3f5325d0a08c9ac\" active=\"true\" name=\"Data Access\" ><h3 id=\"TheChineseMammographyDatabase(CMMD)-DataAccess\">Data Access<\/h3><div class=\"table-wrap\"><table class=\"wrapped confluenceTable\"><colgroup><col\/><col\/><col\/><\/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\"><p>Images (DICOM, 22.9 GB)<\/p><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p><br\/>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/70230508\/The%20Chinese%20Mammography%20Database.tcia\" 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:\/\/nbia.cancerimagingarchive.net\/nbia-search\/?CollectionCriteria=CMMD\" 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><span style=\"color: rgb(33,37,41);text-decoration: none;\">(Download requires\u00a0<\/span><span style=\"color: rgb(33,37,41);text-decoration: none;\">the<span>\u00a0<\/span><\/span><a rel=\"nofollow\" style=\"text-decoration: none;text-align: left;\" href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\">NBIA Data Retriever<\/a>)<\/p><\/div><\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p class=\"auto-cursor-target\">\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 4.0<\/a><\/p><\/div><\/td><\/tr><tr><td class=\"confluenceTd\">Clinical data (XLSX)<\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p><br\/>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/70230508\/CMMD_clinicaldata_revision.xlsx?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>\n<a href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\" class=\"external-link\" rel=\"nofollow\">CC BY 4.0<\/a><\/p><\/div><\/td><\/tr><\/tbody><\/table><\/div><p>Click the Versions tab for more info about data releases.<\/p><p><span style=\"color: rgb(23,43,77);\">Please contact <a class=\"external-link\" href=\"mailto:help@cancerimagingarchive.net\" rel=\"nofollow\">help@cancerimagingarchive.net<\/a>\u00a0 with any questions regarding usage.<\/span><\/p>\n<h3 id=\"TheChineseMammographyDatabase(CMMD)-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 class=\"xmsonormal\" style=\"text-align: left;\"><br\/><\/p><ul style=\"text-align: left;\"><li class=\"auto-cursor-target\"><a href=\"https:\/\/portal.imaging.datacommons.cancer.gov\/explore\/filters\/?collection_id=cmmd\" class=\"external-link\" rel=\"nofollow\">Imaging Data Commons (IDC)<\/a><span>\u00a0<\/span>(Imaging Data)<\/li><\/ul><p><br\/><\/p><p>Please note, it has been discovered that the hashes for the pixels of the following seem to be identical. TCIA does not know which is the &quot;more correct&quot; case for the files mentioned:<\/p><ul><li>D1-0202 (series UID ending with 31072, 1-1.dcm image) and D2-0284 (seriesUID ending with 98151, 1-1.dcm image)\u00a0<\/li><li>D1-0202 (series UID ending with 31072, 1-2.dcm image) and D2-0284 (seriesUID ending with 98151, 1-2.dcm image)\u00a0<\/li><li>D1-0202 (series UID ending with 31072, 1-3.dcm image) and D2-0284 (seriesUID ending with 98151, 1-3.dcm image)\u00a0<\/li><li>D1-0202 (series UID ending with 31072, 1-4.dcm image) and D2-0284 (seriesUID ending with 98151, 1-4.dcm image)\u00a0<\/li><li>D1-0808 (series UID ending with 62447, 1-1.dcm image) and D1-1292 (series UID ending with 65585, 1-1.dcm image)\u00a0<\/li><\/ul><\/div><div class=\"tabs-pane \" id=\"7023050875edb2c998324525a079f302716bd7c4\" name=\"Detailed Description\" ><h3 id=\"TheChineseMammographyDatabase(CMMD)-DetailedDescription\">Detailed Description<\/h3><div class=\"table-wrap\"><table class=\"wrapped confluenceTable\"><colgroup><col\/><col\/><\/colgroup><tbody><tr><th class=\"confluenceTh\"><p>Image Statistics<\/p><\/th><th class=\"confluenceTh\"><br\/><\/th><\/tr><tr><td class=\"confluenceTd\"><p>Modalities<\/p><\/td><td class=\"confluenceTd\"><p>MG<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Patients<\/p><\/td><td class=\"confluenceTd\"><p>1775<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Studies<\/p><\/td><td class=\"confluenceTd\"><p>1775<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Series<\/p><\/td><td class=\"confluenceTd\"><p>1775<\/p><\/td><\/tr><tr><td class=\"confluenceTd\"><p>Number of Images<\/p><\/td><td class=\"confluenceTd\"><p>5202<\/p><\/td><\/tr><tr><td colspan=\"1\" class=\"confluenceTd\">Images Size (GB)<\/td><td colspan=\"1\" class=\"confluenceTd\">22.9 GB<\/td><\/tr><\/tbody><\/table><\/div><ul style=\"text-align: left;\"><li><span style=\"color: rgb(32,33,36);\">Mammography images were collected in .TIFF format and converted to DICOM.<\/span><\/li><li><span style=\"color: rgb(32,33,36);\">Clinical data are saved in .XLSX format. Note that for those rows where there exists BOTH a value for ID1 and ID2, TCIA image database stores ONLY the ID2 value as PatientID.<br\/><\/span><\/li><li><span style=\"color: rgb(32,33,36);\">For the D2-XXXX dataset, it is a dataset that only involves malignant tumors. Therefore, only one side of the clinical data is reasonable, such a situation shows that the other side is benign. \u00a0We provided mammograms from both the left and right breast.<\/span><\/li><\/ul><p><br\/><\/p><\/div><div class=\"tabs-pane \" id=\"70230508eafc83b6ab624b80900e0f069203bacd\" name=\"Citations BITVOODOO_ANDamp; Data Usage Policy\" ><h3 id=\"TheChineseMammographyDatabase(CMMD)-Citations&amp;DataUsagePolicy\">Citations &amp; Data Usage Policy<\/h3><p>\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>Cui, Chunyan;\u00a0Li Li;\u00a0Cai, Hongmin;\u00a0Fan, Zhihao;\u00a0Zhang, Ling;\u00a0Dan, Tingting;\u00a0Li, Jiao;\u00a0Wang, Jinghua. (2021)\u00a0<strong><span style=\"color: rgb(33,37,41);\">The C<\/span><span style=\"color: rgb(32,31,30);\">hinese Mammography Database (CMMD):\u00a0<\/span><\/strong><span style=\"color: rgb(33,37,41);\"><strong>An online mammography database with biopsy confirmed types for machine diagnosis of breast<\/strong>. The Cancer Imaging Archive. DOI: <\/span><a href=\"https:\/\/doi.org\/10.7937\/tcia.eqde-4b16\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.7937\/tcia.eqde-4b16<\/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>Cai, H., Huang, Q., Rong, W., Song, Y., Li, J., Wang, J., Chen, J., &amp; Li, L. (2019). <strong>Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms.<\/strong> Computational and Mathematical Methods in Medicine, 2019, 1\u201310. <a href=\"https:\/\/doi.org\/10.1155\/2019\/2717454\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1155\/2019\/2717454<\/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>Wang, J., Yang, X., Cai, H., Tan, W., Jin, C., &amp; Li, L. (2016). <strong>Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning.<\/strong> Scientific Reports, 6(1). <a href=\"https:\/\/doi.org\/10.1038\/srep27327\" class=\"external-link\" rel=\"nofollow\">https:\/\/doi.org\/10.1038\/srep27327<\/a><\/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., &amp; Prior, F. (2013). <strong>The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository.<\/strong> Journal of Digital Imaging, 26(6), 1045\u20131057. <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=\"TheChineseMammographyDatabase(CMMD)-OtherPublicationsUsingThisData\">Other Publications Using This Data<\/h3><p><span>TCIA maintains\u00a0<\/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=\"70230508bd92cac178f64248a9af983b338f7743\" name=\"Versions\" ><h3 id=\"TheChineseMammographyDatabase(CMMD)-Version1(Current):Updated2021\/04\/06\">Version 1 (Current): Updated 2021\/04\/06<\/h3><div class=\"table-wrap\"><table class=\"wrapped fixed-table confluenceTable\"><colgroup><col style=\"width: 210.0px;\"\/><col style=\"width: 368.0px;\"\/><\/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 colspan=\"1\" class=\"confluenceTd\"><p>Images (DICOM, 22.9 GB)<\/p><\/td><td colspan=\"1\" class=\"confluenceTd\"><div class=\"content-wrapper\"><p><br\/>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/70230508\/The%20Chinese%20Mammography%20Database.tcia\" 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:\/\/nbia.cancerimagingarchive.net\/nbia-search\/?CollectionCriteria=CMMD\" 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><span style=\"color: rgb(33,37,41);text-decoration: none;\">(Download requires\u00a0<\/span><span style=\"color: rgb(33,37,41);text-decoration: none;\">the<span>\u00a0<\/span><\/span><a href=\"https:\/\/wiki.cancerimagingarchive.net\/display\/NBIA\/Downloading+TCIA+Images\" style=\"text-decoration: none;text-align: left;\" rel=\"nofollow\">NBIA Data Retriever<\/a>)<\/p><\/div><\/td><\/tr><tr><td class=\"confluenceTd\">Clinical data (XLSX)<\/td><td class=\"confluenceTd\"><div class=\"content-wrapper\"><p><br\/>\n\n<span class=\"confluence-embedded-file-wrapper confluence-embedded-manual-size\">\n   <a href=\"https:\/\/wiki.cancerimagingarchive.net\/download\/attachments\/70230508\/CMMD_clinicaldata_revision.xlsx?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><p><br\/><\/p><p><br\/><\/p><p><br\/><\/p><p><br\/><\/p>","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<br\/>\n<li><a href=\"https:\/\/portal.imaging.datacommons.cancer.gov\/explore\/filters\/?collection_id=cmmd\">Imaging Data Commons (IDC)<\/a>\u00a0(Imaging Data)<\/li>\n<br\/>\n<li>D1-0202 (series UID ending with 31072, 1-1.dcm image) and D2-0284 (seriesUID ending with 98151, 1-1.dcm image)\u00a0<\/li>\n<li>D1-0202 (series UID ending with 31072, 1-2.dcm image) and D2-0284 (seriesUID ending with 98151, 1-2.dcm image)\u00a0<\/li>\n<li>D1-0202 (series UID ending with 31072, 1-3.dcm image) and D2-0284 (seriesUID ending with 98151, 1-3.dcm image)\u00a0<\/li>\n<li>D1-0202 (series UID ending with 31072, 1-4.dcm image) and D2-0284 (seriesUID ending with 98151, 1-4.dcm image)\u00a0<\/li>\n<li>D1-0808 (series UID ending with 62447, 1-1.dcm image) and D1-1292 (series UID ending with 65585, 1-1.dcm image)\u00a0<\/li>","cancer_locations":["Breast"],"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> which leverage TCIA data.  If you have a manuscript you'd like to add please<a href=\"http:\/\/www.cancerimagingarchive.net\/support\/\"> contact the TCIA Helpdesk<\/a>.","species":["Human"],"collection_title":"The Chinese Mammography Database","detailed_description":"<ul><li>Mammography images were collected in .TIFF format and converted to DICOM.<\/li><li>Clinical data are saved in .XLSX format. Note that for those rows where there exists BOTH a value for ID1 and ID2, TCIA image database stores ONLY the ID2 value as PatientID.<br\/><\/li><li>For the D2-XXXX dataset, it is a dataset that only involves malignant tumors. Therefore, only one side of the clinical data is reasonable, such a situation shows that the other side is benign. \u00a0We provided mammograms from both the left and right breast.<\/li><\/ul>\n<br\/>","related_analysis_results":false,"subjects":"1775","collection_short_title":"CMMD","data_types":["MG"],"date_updated":"2023-09-13","collection_browse_title":"","supporting_data":["Clinical"],"collection_featured_image":{"ID":"8433","post_author":"6","post_date":"2023-09-13 04:10:37","post_date_gmt":"2023-09-13 04:10:37","post_content":"","post_title":"Inclusion_exclusion_criteria","post_excerpt":"","post_status":"inherit","comment_status":"open","ping_status":"closed","post_password":"","post_name":"inclusion_exclusion_criteria","to_ping":"","pinged":"","post_modified":"2023-09-13 12:04:41","post_modified_gmt":"2023-09-13 12:04:41","post_content_filtered":"","post_parent":"5718","guid":"https:\/\/cm.vastapps.dev\/wp-content\/uploads\/Inclusion_exclusion_criteria.png","menu_order":"0","post_type":"attachment","post_mime_type":"image\/png","comment_count":"0","pod_item_id":"8433"},"collection_summary":"Breast carcinoma is the second largest cancer in the world among women. Early detection of breast cancer has been shown to increase the survival rate, thereby significantly increasing patients' lifespans. Mammography, a noninvasive imaging tool with low cost, is widely used to diagnose breast disease at an early stage due to its high sensitivity. The recent popularization of artificial intelligence in computer-aided diagnosis creates opportunities for advances in areas such as\u00a0(1) Computer-aided detection for locating suspect lesions such as mass and microcalcification, leaving the classification to the radiologist; and (2) Computer-aided diagnosis for characterizing the suspicious region of lesion and\/or estimate its probability of onset; and (3) Findings of predictive image-based biomarkers by applying the computational methods to mine the potential relationships between image representation and molecular subtype, including luminal A, luminal B, HER2 positive, and Triple-negative.<p>However, existing publicly available mammography databases are limited by small sample size, lack of diversity in patient populations, missing biopsy confirmations and unknown molecular sub-types.\u00a0\u00a0To help fill the gap, we built a database\u00a0conducted on 1,775 patients from China with benign or malignant breast disease who underwent mammography examination between July 2012 and January 2016. The database consists of 3,728 mammographies from these 1,775 patients, with biopsy confirmed type of benign or malignant tumors. For 749 of these patients (1,498 mammographies) we also include patients' molecular subtypes. Image\u00a0data were acquired on a GE Senographe DS mammography system.\u00a0\u00a0<\/p>\n<br\/>","collection_acknowledgements":"<ul><li>The authors of this dataset thank the volunteers from the <strong>School of Computer Science and Engineering, South China University of Technology<\/strong> for assisting to tidy the clinical and imaging data. This work was supported by the grant from the National Natural Science Foundation of China (no.61771007).<\/li><li>This work was partially supported by the <strong>Key-Area Research and Development of Guangdong Province<\/strong> under Grant (2020B010166002, 2020B1111190001), the <strong>National Natural Science Foundation of China<\/strong> (61472145, 61771007), <strong>Guangdong Natural Science Foundation<\/strong> (2017A030312008), and the <strong>Health &amp; Medical Collaborative Innovation Project of Guangzhou City<\/strong> (201803010021, 202002020049).<\/li><li>Harmonization of the components of this dataset, including into standard DICOM representation, was supported in part by the NCI Imaging Data Commons consortium. NCI Imaging Data Commons consortium is supported by the contract number 19X037Q from Leidos Biomedical Research under Task Order HHSN26100071 from NCI.<br\/><br\/><\/li><\/ul>","collection_funding":"","hide_from_browse_table":[],"_links":{"self":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/collections\/5718"}],"collection":[{"href":"https:\/\/cm.vastapps.dev\/api\/v1\/collections"}],"about":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/types\/tcia_collection"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/media\/8433"}],"wp:attachment":[{"href":"https:\/\/cm.vastapps.dev\/api\/wp\/v2\/media?parent=5718"}],"wp:term":[{"taxonomy":"tcia_citation_tax","embeddable":true,"href":"https:\/\/cm.vastapps.dev\/api\/v1\/citation-tax?post=5718"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}