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New software using artificial intelligence analysis may become a milestone in diagnosing lung cancer


The software that helps in the early detection of cancer by applying artificial intelligence to automatically analyze CT images and that was developed in cooperation between Semmelweis University (SE), Ulyssys Ltd. and the ELKH Institute for Computer Science and Control (SZTAKI) may become a milestone in lung cancer diagnostics. The software enables automatic and rapid diagnostic analysis of chest CT scans, allowing orders of magnitude more CT scans to be evaluated while reducing the workload for doctors. The project is based on the segmentation of 8,300 low-dose chest radiographs taken at the university clinic and the hospitals of Balassagyarmat, Miskolc, Salgótarján, Nyíregyháza, Szolnok and Baja.

According to Béla Merkely, Rector of Semmelweis University the plan is to extend the program to cover complex examination of the thoracic organs and diagnosing other diseases of the heart and lungs. He also stressed that universities have become internationally recognized centers of knowledge through education, research and innovation, and medicine, and this makes Semmelweis University the most successful institution in higher education rankings in Central Europe. Their fundamental aim is to keep up with international trends in all three areas, to make the technology of the future available and to provide a healthy, inspiring environment for students, patients and staff that supports innovation.


This internationally cutting-edge development is another step towards achieving their goal of becoming one of the top one hundred medical universities in the world and among the top five in Europe. Péter Takács, Minister of State for Health of the Ministry of the Interior emphasized that he considers medical universities as a strong ally and wishes to build on their knowledge in medicine, research and education. Medical universities are an indispensable part of the Hungarian healthcare system and one of the most important areas of innovation. The cooperation between Semmelweis University and the hospitals of the National Hospital Directorate is exemplary, said Péter Takács. Then he added that in the public health sector human resources will be the ‘bottleneck’ in the coming years, so the aim is to reduce the workload of employees, and artificial intelligence-based decision-support systems can contribute to this. Péter Wellisch, Managing Director of Ulyssys Ltd. spoke at the event about good cooperation between the university research sector and the SME sector. He noted that they have been working on AI solutions for a long time, but they had not previously thought that healthcare would be one of the areas where it could be applied. He added that he could not imagine a more responsible role for an IT professional than to serve the health sector, where the primary concern is to protect human life, provide medical care and support the maintenance of quality of life. Péter Wellisch also said that clinical testing is already in progress and will be completed in a few months. He hopes that the program will be operational in the second half of next year.

Pál Maurovich Horvat, Director of the Medical Imaging Centre of Semmelweis University noted at the event that lung cancer is one of the leading causes of death in Hungary, with the highest mortality rate in Europe. He also said that the five-year survival rate for lung cancer is greatly influenced by when the tumor is detected.

In the course of the project SZTAKI supported the accuracy of the machine-learning algorithm for diagnostics with two neural network-based solutions, which makes it possible to increase the resolution of CT images and to artificially generate additional images suitable for teaching the system. In addition, research has been launched in a new area to develop machine-learning methods based on the internal format of the CT scanner, which can detect tumors by eliminating the by-products of image reconstruction.

The Hungarian government provided HUF 1.448 billion in EU funding for the project, which was implemented under the Széchenyi 2020 program.