Adaptive two-way sweeping method to 3D kidney reconstruction

Objective: This article presents a novel method of automatic kidney contour detection in computed tomography angiography images. This technique allows to read as input the entire set of CTA images. It allows to read an entire set of kidney CTA images as input and then automatically generates binary images of the detected kidney outlines for each scan separately. Its additional feature is a real-time 3D kidney model reconstruction. Methods: The main idea is based on an innovative two-way scanning technique. To adapt an algorithm, a CT is analyzed on the basis of a previous slice. The final kidney contour recognition uses the following digital image processing techniques: mathematical morphology, region growth, colorization. Results: to assess the quality of our technique, we consulted the results with a pathology department. The F1 score of the researched method is 88 % compared to human specialist's verification. We also conducted a comparative study of computation time, system reliability, and recognition accuracy using three recent alternative methods. Conclusion: In comparison to machine learning algorithms, the presented method is very precise thanks to the application of the adaptive sweeping technique. This solution can be successfully applied in CTA image analyzing, visualization, and neoplastic changes detection. Significance: computer-aided medical diagnostic is currently one of the greatest challenges for biomedical engineers. The technique can find a real-life application in medical centers and medical-pathology departments.