Title :
Helical CT of von Hippel-Lindau: semi-automated segmentation of renal lesions
Author :
Summers, Ronald M. ; Agcaoili, Cecily M L ; McAuliffe, Matthew J. ; Dalal, Sarang S. ; Yim, Peter J. ; Choyke, Peter L. ; Walther, McClellan M. ; Linehan, W.
Author_Institution :
Nat. Cancer Inst., Nat. Inst. of Health, Bethesda, MD, USA
Abstract :
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 (± sd) numbers of interior and exterior manually placed contours required to perform a complete watershed segmentation of the kidneys were 2.2 ±1.2 and 1.2 ±0.6, respectively. The mean difference between the watershed and manual methods of computing renal volume was 13 ±18 mL (5 ±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)
Keywords :
computerised tomography; diseases; genetics; image segmentation; interactive systems; kidney; mathematical morphology; medical image processing; tumours; cysts; genetic research; granulometry; helical CT; hereditary cystic diseases; interactive marker-controlled algorithm; kidney lesions; mathematical morphology; renal lesions; semi-automated segmentation; solid tumors; thresholding; von Hippel-Lindau disease; watershed algorithm; Computed tomography; Diseases; Genetics; Image analysis; Image edge detection; Image processing; Lesions; Neoplasms; Radiology; Solids;
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
DOI :
10.1109/ICIP.2001.958485