Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Deep Learning Histology Pattern Recognition for Healthcare and Drug Discovery

2,282 views

Published on

Deep learning visual recognition technology can be applied to accurately detect cancer patterns on histology tissue slides. This application of deep learning visual recognition technology opens new opportunities in personalized cancer therapy and drug discovery.

Published in: Healthcare
  • My friend sent me a link to to tis site. This awesome company. They wrote my entire research paper for me, and it turned out brilliantly. I highly recommend this service to anyone in my shoes. ⇒ www.HelpWriting.net ⇐.
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • My brother found Custom Writing Service ⇒ www.WritePaper.info ⇐ and ordered a couple of works. Their customer service is outstanding, never left a query unanswered.
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • Very nice tips on this. In case you need help on any kind of academic writing visit our website ⇒ HelpWriting.net ⇐ and place your order
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • DOWNLOAD THAT BOOKS INTO AVAILABLE FORMAT (2019 Update) ......................................................................................................................... ......................................................................................................................... Download Full PDF EBOOK here { http://bit.ly/2m6jJ5M } ......................................................................................................................... Download Full EPUB Ebook here { http://bit.ly/2m6jJ5M } ......................................................................................................................... Download Full doc Ebook here { http://bit.ly/2m6jJ5M } ......................................................................................................................... Download PDF EBOOK here { http://bit.ly/2m6jJ5M } ......................................................................................................................... Download EPUB Ebook here { http://bit.ly/2m6jJ5M } ......................................................................................................................... Download doc Ebook here { http://bit.ly/2m6jJ5M } ......................................................................................................................... ......................................................................................................................... ................................................................................................................................... eBook is an electronic version of a traditional print book that can be read by using a personal computer or by using an eBook reader. (An eBook reader can be a software application for use on a computer such as Microsoft's free Reader application, or a book-sized computer that is used solely as a reading device such as Nuvomedia's Rocket eBook.) Users can purchase an eBook on diskette or CD, but the most popular method of getting an eBook is to purchase a downloadable file of the eBook (or other reading material) from a Web site (such as Barnes and Noble) to be read from the user's computer or reading device. Generally, an eBook can be downloaded in five minutes or less ......................................................................................................................... .............. Browse by Genre Available eBooks .............................................................................................................................. Art, Biography, Business, Chick Lit, Children's, Christian, Classics, Comics, Contemporary, Cookbooks, Manga, Memoir, Music, Mystery, Non Fiction, Paranormal, Philosophy, Poetry, Psychology, Religion, Romance, Science, Science Fiction, Self Help, Suspense, Spirituality, Sports, Thriller, Travel, Young Adult, Crime, Ebooks, Fantasy, Fiction, Graphic Novels, Historical Fiction, History, Horror, Humor And Comedy, ......................................................................................................................... ......................................................................................................................... .....BEST SELLER FOR EBOOK RECOMMEND............................................................. ......................................................................................................................... Blowout: Corrupted Democracy, Rogue State Russia, and the Richest, Most Destructive Industry on Earth,-- The Ride of a Lifetime: Lessons Learned from 15 Years as CEO of the Walt Disney Company,-- Call Sign Chaos: Learning to Lead,-- StrengthsFinder 2.0,-- Stillness Is the Key,-- She Said: Breaking the Sexual Harassment Story That Helped Ignite a Movement,-- Atomic Habits: An Easy & Proven Way to Build Good Habits & Break Bad Ones,-- Everything Is Figureoutable,-- What It Takes: Lessons in the Pursuit of Excellence,-- Rich Dad Poor Dad: What the Rich Teach Their Kids About Money That the Poor and Middle Class Do Not!,-- The Total Money Makeover: Classic Edition: A Proven Plan for Financial Fitness,-- Shut Up and Listen!: Hard Business Truths that Will Help You Succeed, ......................................................................................................................... .........................................................................................................................
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • DOWNLOAD FULL BOOKS, INTO AVAILABLE FORMAT ......................................................................................................................... ......................................................................................................................... ,DOWNLOAD FULL. PDF EBOOK here { https://tinyurl.com/yyxo9sk7 } ......................................................................................................................... ,DOWNLOAD FULL. EPUB Ebook here { https://tinyurl.com/yyxo9sk7 } ......................................................................................................................... ,DOWNLOAD FULL. doc Ebook here { https://tinyurl.com/yyxo9sk7 } ......................................................................................................................... ,DOWNLOAD FULL. PDF EBOOK here { https://tinyurl.com/yyxo9sk7 } ......................................................................................................................... ,DOWNLOAD FULL. EPUB Ebook here { https://tinyurl.com/yyxo9sk7 } ......................................................................................................................... ,DOWNLOAD FULL. doc Ebook here { https://tinyurl.com/yyxo9sk7 } ......................................................................................................................... ......................................................................................................................... ......................................................................................................................... .............. Browse by Genre Available eBooks ......................................................................................................................... Art, Biography, Business, Chick Lit, Children's, Christian, Classics, Comics, Contemporary, Cookbooks, Crime, Ebooks, Fantasy, Fiction, Graphic Novels, Historical Fiction, History, Horror, Humor And Comedy, Manga, Memoir, Music, Mystery, Non Fiction, Paranormal, Philosophy, Poetry, Psychology, Religion, Romance, Science, Science Fiction, Self Help, Suspense, Spirituality, Sports, Thriller, Travel, Young Adult,
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here

Deep Learning Histology Pattern Recognition for Healthcare and Drug Discovery

  1. 1. Visual Recognition of Tissue Patterns on Pathology Slides web-pathology.net FOR HEALTHCARE AND DRUG DISCOVERY SMART IMAGING TECHNOLOGIES
  2. 2. Personalized Cancer Therapy: Knowledge Path Personalized Therapy Medical History and Personal Information Genetic Information Pathology Information (tumor biomarkers) Personalized cancer therapy is a treatment strategy centered on the ability to predict which patients are more likely to respond to specific cancer therapies. This approach is founded upon the idea that tumor biomarkers are associated with patient prognosis and tumor response to therapy. In addition, patient genetic factors can be associated with drug metabolism, drug response and drug toxicity. Personalized tumor molecular profiles, tumor disease site and other patient characteristics are then potentially used for determining optimum individualized therapy options. Source: MD Anderson Cancer Center Pathology, the “study of disease”, is an essential component for analysis of personalized cancer therapy options Needs for Healthcare FOR HEALTHCARE
  3. 3. Diagnostic Pattern Library: Applications and Benefits Classified cancer pattern library is valuable digital asset that can be licensed to other parties to train visual recognition and image analysis algorithms. Visual recognition application can be used to automatically annotate digital pathology slides and link them with the rest of institutional cancer knowledge base. This application can be licensed to third parties to use for the same purposes. Research and Clinical Applications: • Computer-assisted cancer diagnosis with pre-screening, suggestive diagnosis options and contextual links to cancer knowledge libraries (similar cases, experts, research, additional tests etc.) • Data mining and of advanced analytics of historic tissue samples for cancer patients with known outcomes with purpose of building predictive knowledge bases for cancer care and drug discovery FOR HEALTHCARE
  4. 4. Researchers need to measure drug effects on tissue. They also need to analyze relationships between effect on tissue and all other relevant data in the drug research project. Drug effects on tissue are expressed via biomarker patterns on tissue slides. Researchers need to turn visual pattern expression into usable data. They need technology to: • Objectify pattern definitions to deal with subjective biases of human observers • Search for similar biomarker expression patterns across archives • Aggregate, analyze and organize pattern expression information • Link pattern information to other “omnics” and project research data Needs for Drug Discovery FOR DRUG DISCOVERY
  5. 5. Utilizing Pathology Knowledge: The Challenge Traditionally, pathology diagnosis is presented in descriptive natural language statements. Often It is verbose professional opinion of human expert with little quantitative information Statistical agreement between human experts is 75%-85%. Pathology diagnosis is rendered by pathologist observing patterns of cells on tissue slide under the microscope. In order to be useful for comparison and analysis these observations must be: • Quantified • Objectified This can be achieved (in theory) by digitizing pathology slide and applying image analysis algorithms to quantify cell pattern expressions.
  6. 6. Analyzing Pathology Slides: The Real Life Issues In practice traditional image analysis approach often fall short of expectations for number of reasons: • Target image features are complex and difficult for engineers to formalize and code. • Algorithm development process is inherently complicated: only pathologists know that patterns they need but only image analysis engineers may know how to extract them • Tissues have variability and algorithms developed on one sample may not work on others. Algorithms have to be redesigned by engineers every time new “out of range” samples are encountered • Digital tissue slides are very large and processing every pixel is extremely computationally expensive, making “online” analysis impossible or impractical
  7. 7. Analyzing Pathology Slides: Machine Learning Machine Learning Neural Networks learn to recognize images in the same way humans do – by example, rather than by formalized “handcrafted features”. Since 2012 major improvement in visual recognition was achieved with so called deep learning neural networks. Latest generation of Visual Recognition Neural Networks achieve accuracy of recognition of natural objects similar to human observers. This area of technology is experiencing explosive growth. Using Machine Learning brings number of advantages to visual recognition applications: • No need to formalize complex “handcrafted features”, pathologist can just point to patterns they need to recognize • No dependency on image analysis engineers (almost) • System can be trained on very large number of samples to achieve robust recognition • New data samples can be added to model easily to increase accuracy
  8. 8. Machine Learning: Requirements Machine Learning approach to pattern recognition creates new functional requirements for digital pathology software • Robust visual recognition models need large number of training images which requires more time for annotating than single pathologist can provide. This problem can be solved by utilizing number of pathologists creating annotations for training visual recognition models Collaborative Model Training (Crowdsourcing) • Digital Pathology system should have capability for extracting specially formatted image data sets on demand for training neural networks Training Data Extraction • Training of Neural Network requires massive parallel GPU computing power for a short time. This scalable computing power can be economically delivered by scalable cloud infrastructures such as IBM, Amazon or Microsoft. Cloud Deployment • Digital pathology software should be able to send imaging data to neural network application for recognition and visualize responses for user. API Integration and Visualization Interface
  9. 9. The Solution: Pattern Recognition with Machine Learning • Last generation deep learning convolution networks can identify target tissue patters with 95% accuracy Deep Learning • Pathologists can train recognition solution by simply annotating target tissue patters on slides in their workspace • They can easily set up classes of patterns for identification Easy Training • Robust solutions can be trained from multiple slides to identify target tissue patterns reliably across large variety of samples • Recognition models can be retrained easily if new patterns or different samples should be added Robust Recognition Models • Slides in digital archives can be processed automatically for pattern detection and labeled based on findings • New slides can be analyzed and classified on upload with suggestive classification available when human expert opens the slide Automatic Processing • Visualization overlays help quickly locate and review target patterns • Visualization layer provides quantitative information about patterns Advanced Visualization • All data is stored in the database and available for search, data mining and analytics Powerful Analytics Our software can train neural networks and utilize latest deep learning visual recognition solutions from best in class solution providers
  10. 10. The Solution: How it works • Human experts mark areas with target patterns on digital slides in the web interface • Multiple people across geographic locations can work on the same slide library at the same time • Software automatically prepares and extracts imaging data for training visual recognition model in appropriate format • Massive amount of training data can be produced quickly and efficiently with crowdsourcing approach 1. Preparation of Training Data • We train visual recognition models using proven templates and best-in-class machine learning service providers 2. Training Visual Recognition Model • Tissues on new slides coming to server are automatically recognized against known taxonomy and labeled according to application logic. 3. Automatic Recognition Processing • Users can mark the area and search for similar patterns on the same slide or across entire slide archive 4. Search by Example • Software shows identified patterns on slides using interactive “smart” overlays and computes statistics 5. Viewing Results • Users can correct visual recognition results by marking area with appropriate label. New data will be added to the training set to improve recognition 6. Continuous Learning
  11. 11. Integration: Data Mining and Discovery • Non SQL flexible indexed database architecture allows integrated storage of different data items across multiple locations Distributed Database • Flexible structure allows storing and integrating various data in the single information store • New data can be added to database structure at any time Comprehensive Data • Selection and navigation is possible for any data item in the database • Global search on any data is instant even for millions of items Instant Search and Navigation • Data items can be linked with external data sources and knowledge bases such as diagnostic codes, SNOMED classifications or proprietary knowledge bases Data Linking We provide instant search, navigation and data mining ability across millions of slides

×