This article presents a novel multiple organ localization and tracking technique applied to spleen and kidney regions in computed tomography images. The proposed solution is based on a unique approach to classify regions in different spatial projections using convolutional neural networks. The system is able to recognize the contour of the organ with an accuracy of 88-89% depending on the body organ and can compete with U-Net based solutions in terms of hardware requirements. Additionally, it gives better results in small data sets and has a significantly lower training time on an equally sized data set. The proposed system enables visualization, localization and tracking of organs and is therefore a valuable tool in medical diagnostic problems.
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