{"id":31638,"date":"2017-05-29T19:26:51","date_gmt":"2017-05-29T16:26:51","guid":{"rendered":"https:\/\/www.altoros.com\/blog\/?p=31638"},"modified":"2018-11-29T14:32:32","modified_gmt":"2018-11-29T11:32:32","slug":"cross-modal-machine-learning-as-a-way-to-prevent-improper-pathology-diagnostics","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/cross-modal-machine-learning-as-a-way-to-prevent-improper-pathology-diagnostics\/","title":{"rendered":"Cross-Modal Machine Learning as a Way to Prevent Improper Pathology Diagnostics"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.altoros.com\/blog\/cross-modal-machine-learning-as-a-way-to-prevent-improper-pathology-diagnostics\/#Why_is_analysis_of_medical_images_difficult\" >Why is analysis of medical images difficult?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.altoros.com\/blog\/cross-modal-machine-learning-as-a-way-to-prevent-improper-pathology-diagnostics\/#Cross-modal_learning_for_image_segmentation\" >Cross-modal learning for image segmentation<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.altoros.com\/blog\/cross-modal-machine-learning-as-a-way-to-prevent-improper-pathology-diagnostics\/#Want_details_Watch_the_video\" >Want details? Watch the video!<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.altoros.com\/blog\/cross-modal-machine-learning-as-a-way-to-prevent-improper-pathology-diagnostics\/#Related_slides\" >Related slides<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.altoros.com\/blog\/cross-modal-machine-learning-as-a-way-to-prevent-improper-pathology-diagnostics\/#Further_reading\" >Further reading<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.altoros.com\/blog\/cross-modal-machine-learning-as-a-way-to-prevent-improper-pathology-diagnostics\/#About_the_expert\" >About the expert<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"Why_is_analysis_of_medical_images_difficult\"><\/span>Why is analysis of medical images difficult?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Machine learning techniques are widely employed to aid doctors in diagnosing. Still, enabling precise image recognition and analysis can be a really painful experience. This blog post explores why it happens and seeks the ways out as discussed at <a href=\"https:\/\/www.altoros.com\/blog\/tag\/tensorbeat\/\">TensorBeat 2017<\/a>.<\/p>\n<p><a href=\"https:\/\/www.linkedin.com\/in\/davesinghal\/\" target=\"_blank\">Dave Singhal<\/a> talked about the challenges of applying machine learning to <a href=\"https:\/\/www.altoros.com\/blog\/recurrent-neural-networks-classifying-diagnoses-with-long-short-term-memory\/\">improve diagnostics<\/a>. In particular, identifying good vs. bad pathologies to prevent unnecessary removal of an organ or dealing with pathologies that spread to different organs.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/dave-singhal-the-challenges-of-cross-modal-machine-learning-in-tensorflow-healthcare-v1.jpg\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/dave-singhal-the-challenges-of-cross-modal-machine-learning-in-tensorflow-healthcare-v1-1024x678.jpg\" alt=\"\" width=\"640\" class=\"aligncenter size-large wp-image-31640\" \/><\/a><\/center><\/p>\n<p><a href=\"https:\/\/www.altoros.com\/blog\/image-and-text-recognition-with-tensorflow-using-convolutional-neural-networks\/\">Image recognition<\/a> in healthcare is anything but an easy task with indistinct edges, numerous tiny elements, low contrast, etc. In addition to that, medical data comes in multiple forms\u2014MRI, sonograms, <a href=\"https:\/\/www.altoros.com\/blog\/experimenting-with-deep-neural-networks-for-x-ray-image-segmentation\/\">X-rays<\/a>, etc.\u2014with different modalities.<\/p>\n<p>However, the spectrum of machine learning tools is diverse enough to address such tasks as:<\/p>\n<ul>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/using-convolutional-neural-networks-and-tensorflow-for-image-classification\/\">classification<\/a><\/li>\n<li>detection<\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/experimenting-with-deep-neural-networks-for-x-ray-image-segmentation\/\">segmentation<\/a><\/li>\n<li>registration<\/li>\n<li>text + modality<\/li>\n<li>cross-modality<\/li>\n<li>image retrieval, generation, and enhancement<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Cross-modal_learning_for_image_segmentation\"><\/span>Cross-modal learning for image segmentation<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Dave is enthusiastic about exploring the capabilities of what he refers to as <a href=\"https:\/\/arxiv.org\/abs\/1610.09003\" target=\"_blank\">cross-modal learning<\/a>, which is \u201cone model helping the other to do the analysis.\u201d Dave exemplified <a href=\"https:\/\/lmb.informatik.uni-freiburg.de\/people\/ronneber\/u-net\/\" target=\"_blank\">the U-net architecture<\/a> of a <a href=\"https:\/\/www.altoros.com\/blog\/image-and-text-recognition-with-tensorflow-using-convolutional-neural-networks\/\">convolutional neural network<\/a> that ensures fast and precise image segmentation.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/the-u-net-architecture-tensorflow-v11.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/the-u-net-architecture-tensorflow-v11-1024x576.png\" alt=\"\" width=\"640\" class=\"aligncenter size-large wp-image-31642\" \/><\/a><\/center><\/p>\n<p>He also demonstrated what a shared cross-modal representation, which is a set of modal-specific convolutional neural networks, looks like.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/cross-modal-representation-tensorflow-v11.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/cross-modal-representation-tensorflow-v11-1024x576.png\" alt=\"\" width=\"640\" class=\"aligncenter size-large wp-image-31643\" \/><\/a><\/center><\/p>\n<p>However, using such an approach for medical images is challenging as they hardly have sharp features, shapes are mostly not generalizable, edges are gradual, etc.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/the-challenges-of-cross-modal-representation-in-healthcare-v11.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/the-challenges-of-cross-modal-representation-in-healthcare-v11-1024x576.png\" alt=\"\" width=\"640\" class=\"aligncenter size-large wp-image-31644\" \/><\/a><\/center><\/p>\n<p>Dave concluded with an idea of using machine learning for:<\/p>\n<ul>\n<li>cross-segmentation, -representation, -retrieval, and -analysis<\/li>\n<li>cross-visual attention maps<\/li>\n<li>surfacing sub-perceptual (sub-threshold) features<\/li>\n<\/ul>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/dave-singhal-the-challenges-of-cross-modal-machine-learning-in-healthcare-v11.jpg\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2017\/05\/dave-singhal-the-challenges-of-cross-modal-machine-learning-in-healthcare-v11-1024x678.jpg\" alt=\"\" width=\"640\" class=\"aligncenter size-large wp-image-31645\" \/><\/a><\/center><\/p>\n<p>So, machine learning is evolving to save even more lives through helping doctors to avoid mistakes when diagnosing pathologies of different complexities, while automating routine tasks.<\/p>\n<p>Join <a href=\"https:\/\/www.meetup.com\/TensorFlow\/\" target=\"_blank\">our group<\/a> to stay tuned with the upcoming events.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Want_details_Watch_the_video\"><\/span>Want details? Watch the video!<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><center><script src=\"https:\/\/fast.wistia.com\/embed\/medias\/9cfmk3m7lu.jsonp\" async><\/script><script src=\"https:\/\/fast.wistia.com\/assets\/external\/E-v1.js\" async><\/script><\/p>\n<div class=\"wistia_embed wistia_async_9cfmk3m7lu\" style=\"height:360px;width:640px\">&nbsp;<\/div>\n<p><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Related_slides\"><\/span>Related slides<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><center><iframe loading=\"lazy\" src=\"\/\/www.slideshare.net\/slideshow\/embed_code\/key\/tNT80ZyrocoH54\" width=\"595\" height=\"485\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" style=\"border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;\" allowfullscreen><\/iframe><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Further_reading\"><\/span>Further reading<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/tensorflow-and-openpower-driving-faster-cancer-recognition-and-diagnosis\/\">TensorFlow and OpenPOWER Driving Faster Cancer Recognition and Diagnosis<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/recurrent-neural-networks-classifying-diagnoses-with-long-short-term-memory\/\">Recurrent Neural Networks: Classifying Diagnoses with Long Short-Term Memory<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/experimenting-with-deep-neural-networks-for-x-ray-image-segmentation\/\">Experimenting with Deep Neural Networks for X-ray Image Segmentation<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/deep-learning-in-healthcare-finance-and-iiot-tensorflow-use-cases\/\">Deep Learning in Healthcare, Finance, and IIoT: TensorFlow Use Cases<\/a><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"About_the_expert\"><\/span>About the expert<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><small><a href=\"https:\/\/www.linkedin.com\/in\/davesinghal\/\" target=\"_blank\">Dave Singhal<\/a> is an entrepreneur in imaging and machine learning. He is exploring multi-modal medical convolutional neural networks and advising Apricity Health in that area. At Stanford, Dave developed multi-user interaction on a pseudo-holographic display. He holds 10+ patents in areas including imaging, transcoding, displays, and medical image quality metrics.<\/small><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Why is analysis of medical images difficult?<\/p>\n<p>Machine learning techniques are widely employed to aid doctors in diagnosing. Still, enabling precise image recognition and analysis can be a really painful experience. This blog post explores why it happens and seeks the ways out as discussed at TensorBeat 2017.<\/p>\n<p>Dave Singhal talked about [&#8230;]<\/p>\n","protected":false},"author":3,"featured_media":31647,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[214],"tags":[914,117,748,916,749],"class_list":["post-31638","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tutorials","tag-healthcare","tag-iot","tag-machine-learning","tag-tensorbeat","tag-tensorflow"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Cross-Modal Machine Learning as a Way to Prevent Improper Pathology Diagnostics | Altoros<\/title>\n<meta name=\"description\" content=\"This blog post explores how cross-modal learning may help to identify good vs. bad medical pathologies, thus improving diagnostics and treatment.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.altoros.com\/blog\/cross-modal-machine-learning-as-a-way-to-prevent-improper-pathology-diagnostics\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Cross-Modal Machine Learning as a Way to Prevent Improper Pathology Diagnostics | Altoros\" \/>\n<meta property=\"og:description\" content=\"Why is analysis of medical images difficult? 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