Helical CT of von Hippel-Lindau: semi-automated segmentation of renal lesions

• Published in: Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Vol. 2; pp. 293 - 296 vol.2
• Main Authors: Summers, R.M., Agcaoili, C.M.L., McAuliffe, M.J., Dalal, S.S., Yim, P.J., Choyke, P.L., Walther, M.M., Linehan, W.M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2001
• Subjects: Computed tomography; Diseases; Genetics; Image analysis; Image edge detection; Image processing; Lesions; Neoplasms; Radiology; Solids
• ISBN: 0780367251; 9780780367258
• DOI: 10.1109/ICIP.2001.958485

In the setting of von Hippel-Lindau disease, accurate quantitation of kidney lesions is important for genetic research. Unfortunately, fully automated quantitation is difficult because the lesion boundaries are complex. Therefore, we developed a method to semi-automate the quantitation of these renal lesions. We studied helical CT scans of 10 kidneys from 8 patients with von Hippel-Lindau disease. The kidneys were segmented from surrounding structures using an interactive marker-controlled watershed algorithm. Renal lesions (cysts and solid tumors) were identified using thresholding and then characterized by size using mathematical morphology and granulometry. There were 50 cysts and 16 solid lesions. The mean (/spl plusmn/ sd) numbers of interior and exterior manually placed contours required to perform a complete watershed segmentation of the kidneys were 2.2 /spl plusmn/1.2 and 1.2 /spl plusmn/0.6, respectively. The mean difference between the watershed and manual methods of computing renal volume was 13 /spl plusmn/18 mL (5 /spl plusmn/2% of total renal volume) and is not clinically significant. There was no significant difference between volumes of renal lesions measured manually and using the semi-automated method (p > 0.3).