{"id":254,"date":"2025-06-16T18:39:48","date_gmt":"2025-06-16T18:39:48","guid":{"rendered":"https:\/\/radweb.su.domains\/cirp\/?page_id=254"},"modified":"2025-06-16T19:16:28","modified_gmt":"2025-06-16T19:16:28","slug":"birat","status":"publish","type":"page","link":"https:\/\/radweb.su.domains\/cirp\/resources\/birat\/","title":{"rendered":"BiRAT"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"254\" class=\"elementor elementor-254\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-044d613 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"044d613\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-0835e45\" data-id=\"0835e45\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0ed5260 elementor-widget elementor-widget-text-editor\" data-id=\"0ed5260\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2><strong>BiRAT &#8211; Platform for biomedical image registry, analysis, and translation<\/strong><\/h2><p><a href=\"https:\/\/birat.stanford.edu\/\" target=\"_blank\" rel=\"noopener\">https:\/\/birat.stanford.edu\/<\/a><\/p><p>\u00a0<\/p><h3><strong>Background and Motivation<\/strong><\/h3><p>Biomedical imaging in preclinical research often generates large volumes of data across multiple studies, modalities, and time points. This data is essential for analysis, diagnosis, and decision-making in translational research, but its management presents several challenges.<\/p><p><strong>Current Challenges include:<\/strong><\/p><ul><li>Fragmented Data Storage: Researchers store imaging data in local drives, FTP servers, or disconnected archives.<\/li><li>Lack of Standardized Structure: Inconsistent naming, metadata, and folder hierarchies reduce reproducibility.<\/li><li>Manual Tracking: Image metadata and annotations are often logged manually in spreadsheets.<\/li><li>Limited Scalability: Existing solutions don\u2019t support high-volume parallel uploads or nested study hierarchies.<\/li><li>Security Gaps: Sensitive imaging datasets require access control and audit logging, which are typically missing.<\/li><\/ul><p><a href=\"https:\/\/birat.stanford.edu\/\" target=\"_blank\" rel=\"noopener\">The Biomedical Imaging Registry for Analysis &amp; Translation (BiRAT) tool<\/a> was created to address these gaps by offering a secure, scalable software platform for managing biomedical imaging data in preclinical research. The platform enables research institutions to efficiently organize, process, and retrieve high-volume imaging data associated with multi-layered studies. At its core, BiRAT supports a hierarchical data model:<\/p><blockquote><p>Project \u2192 Category\/Study (with optional sub-categories\/studies) \u2192 Image Series \u2192 Files<\/p><\/blockquote><p>This design mirrors the structure of real-world research studies, supporting various modalities (e.g., MRI, PET, CT) and experimental groupings.<\/p><p>The BiRAT web application provides a responsive, role-aware dashboard that enables different users to interact with the system effectively.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7dacc43 elementor-widget elementor-widget-image\" data-id=\"7dacc43\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"872\" height=\"530\" src=\"https:\/\/radweb.su.domains\/cirp\/wp-content\/uploads\/2025\/06\/Screenshot-2025-06-16-at-2.59.12\u202fPM.png\" class=\"attachment-full size-full wp-image-261\" alt=\"\" srcset=\"https:\/\/radweb.su.domains\/cirp\/wp-content\/uploads\/2025\/06\/Screenshot-2025-06-16-at-2.59.12\u202fPM.png 872w, https:\/\/radweb.su.domains\/cirp\/wp-content\/uploads\/2025\/06\/Screenshot-2025-06-16-at-2.59.12\u202fPM-300x182.png 300w, https:\/\/radweb.su.domains\/cirp\/wp-content\/uploads\/2025\/06\/Screenshot-2025-06-16-at-2.59.12\u202fPM-768x467.png 768w\" sizes=\"(max-width: 872px) 100vw, 872px\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\">Figure 1: BiRAT acts as the central platform for managing and organizing biomedical imaging studies. From a black-box perspective, it exposes secure APIs and a web interface, receiving imaging data from users and interfacing with external systems for storage, authentication and analyses.<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>BiRAT &#8211; Platform for biomedical image registry, analysis, and translation https:\/\/birat.stanford.edu\/ \u00a0 Background and Motivation Biomedical imaging in preclinical research often generates large volumes of data across multiple studies, modalities, and time points. This data is essential for analysis, diagnosis, and decision-making in translational research, but its management presents several challenges. Current Challenges include: Fragmented [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":21,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"ocean_front_end_style_editor":"no","ocean_post_layout":"","ocean_both_sidebars_style":"","ocean_both_sidebars_content_width":0,"ocean_both_sidebars_sidebars_width":0,"ocean_sidebar":"","ocean_second_sidebar":"","ocean_disable_margins":"enable","ocean_add_body_class":"","ocean_shortcode_before_top_bar":"","ocean_shortcode_after_top_bar":"","ocean_shortcode_before_header":"","ocean_shortcode_after_header":"","ocean_has_shortcode":"","ocean_shortcode_after_title":"","ocean_shortcode_before_footer_widgets":"","ocean_shortcode_after_footer_widgets":"","ocean_shortcode_before_footer_bottom":"","ocean_shortcode_after_footer_bottom":"","ocean_display_top_bar":"default","ocean_display_header":"default","ocean_header_style":"","ocean_center_header_left_menu":"","ocean_custom_header_template":"","ocean_custom_logo":0,"ocean_custom_retina_logo":0,"ocean_custom_logo_max_width":0,"ocean_custom_logo_tablet_max_width":0,"ocean_custom_logo_mobile_max_width":0,"ocean_custom_logo_max_height":0,"ocean_custom_logo_tablet_max_height":0,"ocean_custom_logo_mobile_max_height":0,"ocean_header_custom_menu":"","ocean_menu_typo_font_family":"","ocean_menu_typo_font_subset":"","ocean_menu_typo_font_size":0,"ocean_menu_typo_font_size_tablet":0,"ocean_menu_typo_font_size_mobile":0,"ocean_menu_typo_font_size_unit":"px","ocean_menu_typo_font_weight":"","ocean_menu_typo_font_weight_tablet":"","ocean_menu_typo_font_weight_mobile":"","ocean_menu_typo_transform":"","ocean_menu_typo_transform_tablet":"","ocean_menu_typo_transform_mobile":"","ocean_menu_typo_line_height":0,"ocean_menu_typo_line_height_tablet":0,"ocean_menu_typo_line_height_mobile":0,"ocean_menu_typo_line_height_unit":"","ocean_menu_typo_spacing":0,"ocean_menu_typo_spacing_tablet":0,"ocean_menu_typo_spacing_mobile":0,"ocean_menu_typo_spacing_unit":"","ocean_menu_link_color":"","ocean_menu_link_color_hover":"","ocean_menu_link_color_active":"","ocean_menu_link_background":"","ocean_menu_link_hover_background":"","ocean_menu_link_active_background":"","ocean_menu_social_links_bg":"","ocean_menu_social_hover_links_bg":"","ocean_menu_social_links_color":"","ocean_menu_social_hover_links_color":"","ocean_disable_title":"default","ocean_disable_heading":"default","ocean_post_title":"","ocean_post_subheading":"","ocean_post_title_style":"","ocean_post_title_background_color":"","ocean_post_title_background":0,"ocean_post_title_bg_image_position":"","ocean_post_title_bg_image_attachment":"","ocean_post_title_bg_image_repeat":"","ocean_post_title_bg_image_size":"","ocean_post_title_height":0,"ocean_post_title_bg_overlay":0.5,"ocean_post_title_bg_overlay_color":"","ocean_disable_breadcrumbs":"default","ocean_breadcrumbs_color":"","ocean_breadcrumbs_separator_color":"","ocean_breadcrumbs_links_color":"","ocean_breadcrumbs_links_hover_color":"","ocean_display_footer_widgets":"default","ocean_display_footer_bottom":"default","ocean_custom_footer_template":"","footnotes":""},"class_list":["post-254","page","type-page","status-publish","hentry","entry"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - aioseo.com -->\n\t<meta name=\"description\" content=\"BiRAT \u2013 Platform for biomedical image registry, analysis, and translationhttps:\/\/birat.stanford.edu\/ Background and MotivationBiomedical imaging in preclinical research often generates large volumes of data across multiple studies, modalities, and time points. This data is essential for analysis, diagnosis, and decision-making in translational research, but its management presents several challenges.Current Challenges include:Fragmented Data Storage: Researchers store imaging data\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<link rel=\"canonical\" href=\"https:\/\/radweb.su.domains\/cirp\/resources\/birat\/\" \/>\n\t\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 5.0.3\" \/>\n\t\t<meta property=\"og:locale\" content=\"en_US\" \/>\n\t\t<meta property=\"og:site_name\" content=\"Co-Clinical Research for Imaging Tumor Associated Macrophages - U24CA264298\" \/>\n\t\t<meta property=\"og:type\" content=\"article\" \/>\n\t\t<meta property=\"og:title\" content=\"BiRAT - Co-Clinical Research for Imaging Tumor Associated Macrophages\" \/>\n\t\t<meta property=\"og:description\" content=\"BiRAT \u2013 Platform for biomedical image registry, analysis, and translationhttps:\/\/birat.stanford.edu\/ Background and MotivationBiomedical imaging in preclinical research often generates large volumes of data across multiple studies, modalities, and time points. 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