Abstract
Ultrasound is the mainstay of imaging for pediatric hydronephrosis, which appears as the dilation of the renal collecting system. However, its potential as diagnostic tool is limited by the subjective visual interpretation of radiologists. As a result, the severity of hydronephrosis in children is evaluated by invasive and ionizing diuretic renograms. In this paper, we present the first complete framework for the segmentation and quantification of renal structures in 3D ultrasound images, a difficult and barely studied challenge. In particular, we propose a new active contour-based formulation for the segmentation of the renal collecting system, which mimics the propagation of fluid inside the kidney. For this purpose, we introduce a new positive delta detector for ultrasound images that allows to identify the fat of the renal sinus surrounding the dilated collecting system, creating an alpha shape-based patient-specific positional map. Finally, we incorporate a Gabor-based semi-automatic segmentation of the kidney to create the first complete ultrasound-based framework for the quantification of hydronephrosis. The promising results obtained over a dataset of 13 pathological cases (dissimilarity of 2.8 percentage points on the computation of the volumetric hydronephrosis index) demonstrate the potential utility of the new framework for the non-invasive and non-ionizing assessment of hydronephrosis severity among the pediatric population.
Chapter PDF
Similar content being viewed by others
References
Peters, C., Chevalier, R.: Congenital Urinary Obstruction: Pathophysiology and Clinical Evaluation. In: Wein, A., Kavoussi, L., Novick, A., Partin, A., Peters, C. (eds.) Campbell-Walsh Textbook of Urology, vol. 4, pp. 3028–3047. Elsevier, Inc, Philadelphia
Fernbach, S.K., et al.: Ultrasound Grading of Hydronephrosis: Introduction to the System Used by the Society for Fetal Urology. Pediatric Radiology 23(6), 478–480
Shapiro, S., et al.: Hydronephrosis Index: A New Method to Track Patients with Hydronephrosis Quantitatively. Urology 72(3), 536–538 (2008)
Cerrolaza, J.J., et al.: Ultrasound Based Computer-Aided-Diagnosis of Kidneys for Pediatric Hydronephrosis. SPIE Medical Imaging, paper 9035-102 (2014)
Noble, J.A., et al.: Ultrasound image segmentation: a survey. IEEE Trans. on Med. Imag. 25(8), 987–1009 (2006)
Mendoza, C.S., et al.: Automatic Analysis of Pediatric Renal Ultrasound Using Shape, Anatomical and Image Acquisition Priors. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds.) MICCAI 2013, Part I. LNCS, vol. 8151, pp. 259–266. Springer, Heidelberg (2013)
Cerrolaza, J.J., et al.: Segmentation of Kidney in 3D-Ultrasound Images Using Gabor-based Appearance Models. In: IEEE Int. Symp. on Biom. Imag., 633–636 (2014)
Caselles, V., et al.: Geodesic Active Contours. Int. Journal of Comp. Vis. 22(1), 61–79 (1997)
Felsberg, M., Sommer, G.: The Monogenic Signal. IEEE Trans. on Sig. Proc. 49(12), 3136–3144 (2001)
Belaid, A., et al.: Phase-Based Level Set Segmentation of Ultrasound Images. IEEE. Trans. on Inf. Tech. in Biomed. 15(1), 138–147 (2011)
Chan, T.F., Vese, L.A.: Active Contours Without Edges. IEEE Trans. Image Proc. 10(2), 266–277 (2001)
Rajpoot, K., et al.: Local-Pase Based 3D Boundary Detection Using Monogenic Signal and its Application to Real-Time 3-D Echocardiography Images. IEEE ISBI (2009)
Kovesi, P.: Image Features from Phase Congruency. J. Comput. Vis. Res. 1(3), 1–26 (1999)
Edelsbrunner, H., et al.: On the Shape of a Set of Points in the Plane. IEEE Trans. Inf. Theory 29(4), 551–559 (1983)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Cerrolaza, J.J., Meyer, C., Jago, J., Peters, C., Linguraru, M.G. (2015). Positive Delta Detection for Alpha Shape Segmentation of 3D Ultrasound Images of Pathologic Kidneys. In: Navab, N., Hornegger, J., Wells, W., Frangi, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science(), vol 9351. Springer, Cham. https://doi.org/10.1007/978-3-319-24574-4_85
Download citation
DOI: https://doi.org/10.1007/978-3-319-24574-4_85
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24573-7
Online ISBN: 978-3-319-24574-4
eBook Packages: Computer ScienceComputer Science (R0)