Autors: Georgieva, V. M., Petrov, P. P., Aleksandar, T. K., Antonia, M. D.
Title: Novel Algorithm for Segmentation of Renal cyst from CT Image Sequence
Keywords: Automatic kidney segmentation, Segmentation of renal cyst.

Abstract: In this paper a novel hybrid segmentation approach for optimization of the renal cyst diagnosis from CT image sequences is proposed. The approach is based on several segmentation techniques. A locally optimized front propagation algorithm according to the level set paradigm with variable term is in the core of the segmentation of the kidney from CT image sequences. Тhe split & merge and color based k-mean clustering algorithms are used for the cyst segmentation. The accuracy evaluation of the renal segmentation with Dice similarity index represents high results for the whole experimental data set – 90, 97%.



    TELSIKS 2019, pp. 380 - 383, 2019, Serbia, Institute of Electrical and Electronics Engineers (IEEE), ISBN 978-1-7281-0877-3 (IEEE)

    Цитирания (Citation/s):
    1. Fuat Türk, Murat Lüy and Necaattin Barisci, "Kidney and Renal Tumor Segmentation Using a Hybrid V-Net-Based Model", Mathematics 2020, Volume 8, Issue 10, October 2020, Article number 1772, Pages 1-17; doi:10.3390/math8101772, - 2020 - в издания, индексирани в Scopus или Web of Science

    Вид: постер/презентация в международен форум, публикация в реферирано издание, индексирана в Scopus