Deep Learning in Processing Medical Images and Calculating the Orbit Volume

A software tool for calculating the volume of a soft-tissue eye orbit using the deep learning of neural network Mask R-CNN has been developed and tested. The result of the development will be in demand when evaluating the results of surgical intervention for the reconstruction of the thin bones of the orbit. It was established that the inaccuracy in constructing the contour of a soft-tissue orbit is 4–8%

Use of the neural network in processing of medical images and calculation of volume of the eye

Представлены результаты исследований по разработке и реализации в виде программного средства поиска глазных яблок и костных структур глазниц. Для достижения цели было использовано глубокое обучение нейронной сети. Показано, что погрешность расчёта объёмов глазниц на основе результатов распознавания орбит нейронной сетью составляет 4–8 %. The results of studies on the development and implementation in the form of a software tool for searching eyeballs and bone structures of the orbits are presented. To achieve the goal, deep neural network training was used. It is shown that the error in calculating the orbit volumes based on the results of the recognition of orbits by the neural network is 4-8%