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Artificial Intelligence-based Structured Heart CT Reporting System

Name of beneficiary

  • Neumann Medical Ltd.
  • Semmelweis University

Project title

Artificial Intelligence-based Structured Heart CT Reporting System

Total financial support for consortium

195 661 864 Ft

Rate of support (percentage)

77,74%

Project launch date

01/01/2020

Planned project end-date

12/31/2021

Full name

Neumann Medical Ltd. (previously Neumann Projekt és Szervezési Ltd.)

Company registration number

01-09-694439

Tax number

12602128-2-42

Location

e1. floor, CityLab, 31, Tűzoltó street, H-1094 Budapest

Project ID number

2019-2.1.10-TÉT-IL-2019-00001

Project Summary

Semmelweis University has launched another high-tech industrial collaboration project with Israeli Arineta and Neumann Medical Ltd. The technology transfer was supported by a grant of HUF 195,661,864 from the National Office for Research, Development and Innovation under the Hungarian-Israeli Industrial R&D Cooperation Tender (code number 2019-2.1.10-TÉT-IL).

The project will develop a structured artificial intelligence-based heart CT scan system in several stages. In the first phase, an integrated coronary artery CT scan clinical workstation software will be created, integrating with the scan workflow process to provide both radiological evaluation and a structured description of the lesions seen, resulting in a clinical finding. In addition, the observed abnormalities and the described clinical abnormalities are combined, so that each abnormality described corresponds exactly to the specific portion of the radiographic imaging on which the radiologist made his or her judgment. The unified workflow, the evaluation of the image elements, and the data collection required for the discovery with the help of the newly created software, thus saving considerable time.

The second step is to create an artificial intelligence platform that provides the optimal environment for analyzing medical images using artificial intelligence. The data collected from the participating health institutes is uploaded anonymously to the central data platform to provide artificial intelligence training. Utilizing the platform’s capabilities, a prototype system is being developed to assist in the identification of coronary plaques and congestions as a decision support system after automatically analyzing new heart CT images. The system provides the opportunity to create full-fledged, automated, artificial intelligence-based tracking systems.