Joint analysis of radiological reports and ct images for automatic validation of pathological brain conditions
Автор: Agafonova Julia Dmitrievna, Gaidel Andrey Viktorovich, Zelter Pavel Mikhailovich, Kapishnikov Aleksandr Viktorovich, Kuznetsov Andrey Vladimirovich, Surovtsev Evgeny Nikolaevich, Nikonorov Artem Vladimirovich
Журнал: Компьютерная оптика @computer-optics
Рубрика: Обработка изображений, распознавание образов
Статья в выпуске: 1 т.47, 2023 года.
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We consider a problem of validation of radiological medical reports and computed tomography images for an automated analysis of brain structures. Two methods for solving the problem are proposed: a method based on the ruCLIP multimodal model, and a method based on the joint use of two separate classifiers - for a text report and for a brain CT image. We discuss methods evaluation and the obtained results. The proposed approaches make it possible to correctly classify 99.6 % of radiological reports from a test sampling into 15 possible diagnoses.
Deep learning, computed tomography, computer-aided diagnosis, pattern recognition, natural language processing
Короткий адрес: https://sciup.org/140296252
IDR: 140296252 | DOI: 10.18287/2412-6179-CO-1201