In vitro assessment of a three-dimensional segmentation algorithm based on the belief functions theory in calculating renal volumes by MR imaging - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue American Journal of Roentgenology Année : 2008

In vitro assessment of a three-dimensional segmentation algorithm based on the belief functions theory in calculating renal volumes by MR imaging

Résumé

OBJECTIVE: Renal volume measurement is an essential part of split renal function assessment in MR urography. The aim of this study was to assess the accuracy and repeatability of a three-dimensional segmentation algorithm based on the belief functions theory for calculating renal volumes from MR images. MATERIALS AND METHODS: The true volume of 20 various sized animal kidneys was obtained by fluid displacement. Each kidney was examined using two different MR units. 3D proton-density weighted-acquisitions with incremental slice thickness were obtained. The MR volume was then measured with a segmentation algorithm based on the belief functions theory. Two independent observers performed all segmentations twice. Accuracy, intra- and inter-observer variability were evaluated by the Bland-Altman method. The number and type of manual corrections were recorded, as well as the entire processing time. RESULTS: The mean renal volume estimated by fluid displacement was 114 mL (range, 38-224 mL). As regards renal volume assessment obtained from adjacent axial MR images, maximal standard deviations of the difference were: 2.2 mL (accuracy), 0.6 mL and 1.8 mL (respectively intra- and inter-observer variability). Segmentation of axial slices provided better accuracy and reproducibility as compared with coronal slices. Overlapped coronal slices yielded poor results due to the partial volume effect. The mean processing time, including optional manual modifications, was less than 75 seconds. CONCLUSION: The belief functions theory could be considered an accurate and reproducible mathematic method to assess renal volume from MR adjacent images.
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Dates et versions

hal-00434331 , version 1 (22-11-2009)

Identifiants

  • HAL Id : hal-00434331 , version 1

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P.-H. Vivier, M. Dolores, Isabelle Gardin, P. Zhang, Caroline Petitjean, et al.. In vitro assessment of a three-dimensional segmentation algorithm based on the belief functions theory in calculating renal volumes by MR imaging. American Journal of Roentgenology, 2008, 191, pp.127-134. ⟨hal-00434331⟩
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