Yissum - Research Development Company of the Hebrew University

Deep Learning Convolutional Neural Network (CNN) for Automatic Detection and Diagnosis of Sacroiliitis in CT Scans

Posted by Yissum - Research Development Company of the Hebrew UniversityResponsive · Innovative Products and Technologies · Israel

Summary of the technology

Deep Learning Convolutional Neural Network (CNN) for Automatic Detection and Diagnosis of Sacroiliitis in CT Scans
Project ID : 19-2019-6737

Description of the technology

Keywords

Sacroiliitis, Sacroiliac joint, Diagnosis, Medical Image Processing, Lower back pain

Current development stage

TRL3 Experimental proof of concept

Application

  • Diagnosis of Sacroiliitis and separation from other types of lower back pain and associated maladies is non-trivial and results, in some cases, in late diagnosis.
  • Numerous CT scans are performed for patients with non-specific lower back pain while the condition goes undiagnosed.
  • Early diagnosis will enable preventive treatment, and reduce costs associated with repeat CT scans and ongoing, ineffective, treatment.

Our Innovation

The research group developed a deep learning convolutional neural network (CNN) for automatic detection and diagnosis of Sacroiliitis in CT scans. The CNN automatically identifies both Sacroliac joints then proceeds to grade the level of Sacroiliitis, in each joint, based on an averaging of grading in each CT slice.

The Advantages

  • Fully automatic
  • Very high sensitivity
  • Grading system based on individual grading per CT slice.

Opportunity

Close to 30% of the population reports lower back pain, many of which are sent for a CT scan for diagnosis

The technology taps this market by addressing this frequently undiagnosed condition. The use of the deep learning CNN will not be limited to patients presenting with Sacroiliitis but potentially to every CT scan performed for patients with an undiagnosed lower back pain.

Project manager

Mel Larrosa
VP Business Development Healthcare

Project researchers

Leo Joskowicz
HUJI, School of Computer Science and Engineering
Computer Science

Related keywords

  • Medicine, Human Health
  • Biology / Biotechnology
  • Genome Research
  • Micro- and Nanotechnology related to Biological sciences
  • Recombinant DNA
  • Monoclonal Antibodies and Hybridomas
  • Gene Splicing and Manufacturing Equipment
  • Other Genetic Engineering
  • Molecular design Market
  • Microbiology Market
  • Micro- and Nanotechnology related to Biological sciences
  • Biochemistry / Biophysics Market
  • Toxicology Market
  • In vitro Testing, Trials Market
  • Stem cells and biobanks
  • Cellular and Molecular Biology Market
  • Population genetics Market
  • Gene Expression, Proteom Research Market
  • Bioinformatics Market
  • Enzymology/Protein Engineering/Fermentation
  • Genetic Engineering Market
  • Diagnostic
  • Therapeutic
  • Other Medical/Health Related
  • Agro and Marine biotech
  • Anatomy, Pathology, Immunology, Physiology
  • Clinical Medicine
  • diagnostics
  • Life Science & Biotechnology

About Yissum - Research Development Company of the Hebrew University

Technology Transfer Office from Israel

Yissum Research Development Company of the Hebrew University of Jerusalem Ltd. Founded in 1964 to protect and commercialize the Hebrew University’s intellectual property. Ranked among the top technology transfer companies, Yissum has registered over 8,900 patents covering 2,500 inventions; has licensed out 800 technologies and has spun-off 90 companies. Products that are based on Hebrew University technologies and were commercialized by Yissum generate today over $2 Billion in annual sales.

Send your request

By clicking "Send your request" you are signing up and accepting our Terms of Service and Privacy policy

Technology Offers on Innoget are directly posted and managed by its members as well as evaluation of requests for information. Innoget is the trusted open innovation and science network aimed at directly connect industry needs with professionals online.