Treatise of Medical Image Processing (TMIP) v0.2.0

Moloti Nakampe

Unknown

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Experiment 2: Coronavirus (2019-nCoV infection) Recognition using Deep Neural Networks for Computer Tomography (CT) image analysis. ...learn more

Project status: Published/In Market

Internet of Things, Artificial Intelligence, Cloud

Intel Technologies
DevCloud, oneAPI, Intel Opt ML/DL Framework, MKL, OpenVINO

Code Samples [1]Links [2]

Overview / Usage

On Dec. 31, 2019, the World Health Organization (WHO) learned of several cases of a respiratory illness clinically resembling viral pneumonia and manifesting as fever, cough, and shortness of breath. The newly discovered virus emerging from Wuhan City, Hubei Province of China, was temporarily named “novel coronavirus” (2019-nCoV). It is now known officially as COVID-19. This new coronavirus belongs to a family of viruses that include Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS).

The outbreak is escalating quickly, with hundreds of thousands of confirmed COVID-19 cases reported globally. Early disease recognition is critical not only for prompt treatment, but also for patient isolation and effective public health containment and response. Thus we propose the use of AI based CT image analysis for recognition of coronavirus infection.

Methodology / Approach

Coronavirus (2019-nCoV infection) recognition using Deep Neural Networks for Computer Tomography (CT) image analysis . Next steps is to work on webapp using webRTC for doctors around the world

Technologies Used

Intel Inside: Intel® Xeon E5-2690 v3 , Intel® MKL-DNN, Intel® Optimized TensorFlow, Intel® Distribution of OpenVINO™ toolkit, Intel® Open Visual Cloud, Intel® DevCloud