Térdporc szegmentálása MR-felvételekből mesterséges intelligencia segítségével = Segmentation of knee cartilages in MR images with artificial intelligence

Szoldán, Péter and Egyed, Zsófia and Szabó, Endre and Somogyi, János and Hangody, György Márk and Hangody, László (2021) Térdporc szegmentálása MR-felvételekből mesterséges intelligencia segítségével = Segmentation of knee cartilages in MR images with artificial intelligence. ORVOSI HETILAP, 162 (9). pp. 352-360. ISSN 0030-6002

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Abstract

Introduction: The partial orthopedic reconstruction of the knee joint with an osteochondral allograft requires precise planning based on medical imaging reliant; an artificial intelligence capable of determining the morphology of the cartilage tissue can be of great help in such a planning. Objective: We aimed to develop and train an artificial intelligence capable of determining the cartilage morphology in a knee joint based on an MR image. Method: After having determined the most appropriate MR sequence to use for this project and having acquired 180 knee MR images, we created the training set for the artificial intelligence by manually and semi-automatically segmenting the contours of the cartilage in the images. We then trained the neural network with this dataset. Results: As a result of our work, the artificial intelligence is capable to determine the morphology of the cartilage tissue in the MR image to a level of accuracy that is sufficient for surgery planning, therefore we have made the first step towards machine-planned surgeries. Conclusion: The selected technology - artificial intelligence - seems capable of solving tasks related to cartilage geometry, creating a wide range of application opportunities in joint therapy. © 2021 Akademiai Kiado Rt.. All rights reserved.

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