{"id":4646,"date":"2025-10-07T14:03:38","date_gmt":"2025-10-07T12:03:38","guid":{"rendered":"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/?p=4646"},"modified":"2026-05-06T23:28:22","modified_gmt":"2026-05-06T21:28:22","slug":"ihc-cell-app-explained","status":"publish","type":"post","link":"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/ihc-cell-app-explained\/","title":{"rendered":"MIKAIA&#8217;s Universal IHC Cell AI App explained"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">The <a href=\"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/mikaia-ihc-cell-detection-app\/\">Universal IHC Cell AI App<\/a> features a universal subcellular IHC cell AI that is compatible with a wide range of markers, tissues, and cell types. Our 23-minute video tutorial guides <a href=\"http:\/\/www.mikaia.ai\">MIKAIA<sup>\u00ae<\/sup><\/a> step by step through the app.<br><\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\" title=\"MIKAIA\u00ae - IHC Cell Detection App Tutorial\" width=\"770\" height=\"433\" src=\"https:\/\/www.youtube.com\/embed\/xOCfijpJWtk?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Time codes of chapters<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em><a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk\">00:00<\/a> Understanding Basic Parameters <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=157s\">02:37<\/a> Tissue Detection <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=218s\">03:38<\/a> Understanding AI Models AI vs. XXL AI <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=299s\">04:59<\/a> Cell Detection: Stain Unmixing &amp; Cell Size <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=417s\">06:57<\/a> Classifying Cells as Positive or Negative <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=609s\">10:09<\/a> Using Filters for \u201cFalse Positives\u201d and \u201cIgnore\u201d Class <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=790s\">13:10<\/a> Computing DAB Expression <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=1025s\">17:05<\/a> Grading of Cells &amp; H-Score <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=1198s\">19:58<\/a> Postprocessing Options: Hotspots <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=1298s\">21:38<\/a> Postprocessing Options: Clusters<\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Introducing the IHC Cell Detection App <\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Contents covered in this first part of the tutorial:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Learn how to use basic parameters.<\/li>\n\n\n\n<li>Start-analysis buttons\n<ul class=\"wp-block-list\">\n<li>Analyze region of interest (RoI), field of view (FoV), slide, and batch.<\/li>\n\n\n\n<li>Re-analyze spreviously selected regions.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>Learn how to view the measured attributes of specific cells.<\/li>\n\n\n\n<li>Understand the differences between the two AI models &#8212; &#8220;AI&#8221; and &#8220;XXL AI&#8221; &#8212; and when to use which.<\/li>\n\n\n\n<li>Stain unmixing<\/li>\n\n\n\n<li>Cell filtering options (e.g., filter by size)<\/li>\n\n\n\n<li>Configuring settings to determine when a cell is classified as positive or negative, including the &#8220;auto&#8221; threshold mode.<\/li>\n\n\n\n<li>Reading and using diagrams with focus on scatter plots.<\/li>\n\n\n\n<li>Using filters for &#8220;false positives&#8221; and the &#8220;ignore&#8221; class.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Classifying membranous or cytoplasmic stains<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Contents covered in this second part of the tutorial (starting at minute <a href=\"https:\/\/www.youtube.com\/watch?v=xOCfijpJWtk&amp;t=790s\">13:10<\/a>):<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Problem<\/strong>: Classifying membrane stains based on average DAB expression across the entire cell is not a reliable foundation for determining positivity and grading cells with membranous or cytoplasmic stains.\n<ul class=\"wp-block-list\">\n<li><strong>Solution 1<\/strong>: Estimate the nucleus by shrinking detected cell contours and determine the average DAB expression separately for both cell compartments. Base positivity decisions solely on expression in the outer compartment.<\/li>\n\n\n\n<li>S<strong>olution 2<\/strong>: Instead of measuring average intensity, focus on the average intensity of the most intensely stained subregion (e.g., the top 20%). <\/li>\n\n\n\n<li>S<strong>olution 3<\/strong>: Combine of solutions 1 and 2.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>Compute <strong>H-score<\/strong>: Enable grading of cells into low, moderate, or strong positive categories.<\/li>\n\n\n\n<li>Optional postprocessing step: Find <strong>hotspots<\/strong>.<\/li>\n\n\n\n<li>Optional postprocessing step: Group nearby positive cells into <strong>clusters<\/strong> and obtain clustering statistics<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>The Universal IHC Cell AI App features a universal subcellular IHC cell AI that is compatible with a wide range of markers, tissues, and cell types. Our 23-minute video tutorial guides MIKAIA\u00ae step by step through the app. Time codes of chapters 00:00 Understanding Basic Parameters 02:37 Tissue Detection 03:38 Understanding AI Models AI vs. [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":4672,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,35,28],"tags":[37,87,7,29,108],"coauthors":[56],"class_list":["post-4646","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-pathology","category-life-science","category-mikaia-university","tag-ai","tag-ihc","tag-mikaia","tag-mikaia-app-note","tag-video-tutorial"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>MIKAIA&#039;s Universal IHC Cell AI App explained<\/title>\n<meta name=\"description\" content=\"This 23-minute tutorial guides MIKAIA users 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