In vitro assessment of a 3D segmentation algorithm based on the belief functions theory in calculating renal volumes by MRI.

Pierre-Hugues Vivier; Michael Dolores; Isabelle Gardin; Peng Zhang; Caroline Petitjean; Jean-Nicolas Dacher

doi:10.2214/AJR.07.3063

In vitro assessment of a 3D segmentation algorithm based on the belief functions theory in calculating renal volumes by MRI.

Pierre-Hugues Vivier ^{1, 2} Michael Dolores ¹ Isabelle Gardin ^{1, 3} Peng Zhang ^{1, 3} Caroline Petitjean ¹ Jean-Nicolas Dacher ^{1, 2}

1 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes

2 Service d'imagerie médicale [Rouen]

3 Service de médecine nucléaire [Rouen]

Abstract : OBJECTIVE: Renal volumetry 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 3D segmentation algorithm based on the belief functions theory for calculating renal volumes from MR images. MATERIALS AND METHODS: The true volumes of 20 animal kidneys of various sizes were obtained by fluid displacement. Each kidney was examined using two different MR units. Three-dimensional proton density-weighted acquisitions with an incremental slice thickness were performed. The MR volume was then measured with a segmentation algorithm based on the belief functions theory. Two independent observers performed all segmentations twice. Accuracy, intraobserver variability, and interobserver 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). With regard to the renal volumes obtained from assessments of adjacent axial MR images, the maximal SDs of the difference were 2.2 mL (accuracy), 0.6 mL (intraobserver variability), and 1.8 mL (interobserver variability). Segmentation of axial slices provided better accuracy and reproducibility than coronal slices. Overlapped coronal slices yielded poor results because of the partial volume effect. The mean processing time including optional manual modifications was less than 75 seconds. CONCLUSION: The belief functions theory can be considered an accurate and reproducible mathematic method to assess renal volume from MR adjacent images.

Type de document :

Article dans une revue

American Journal of Roentgenology, American Roentgen Ray Society, 2008, 191 (3), pp.W127-34. 〈10.2214/AJR.07.3063〉

Domaine :

Sciences du Vivant [q-bio] / Biochimie, Biologie Moléculaire

Liste complète des métadonnées

http://www.hal.inserm.fr/inserm-00472947
Contributeur : Céline Breton <>
Soumis le : mardi 13 avril 2010 - 15:56:45
Dernière modification le : lundi 1 octobre 2018 - 09:58:08

In vitro assessment of a 3D segmentation algorithm based on the belief functions theory in calculating renal volumes by MRI.

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In vitro assessment of a 3D segmentation algorithm based on the belief functions theory in calculating renal volumes by MRI.

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