OBJECTIVE: : During the treatment planning of a preclinical small animal irradiation, which has time limitations for reasons of animal wellbeing and workflow efficiency, the time consuming organ at risk (OAR) delineation is performed manually. This work aimed to develop, demonstrate, and quantitatively evaluate an automated contouring method for six OARs in a preclinical irritation treatment workflow. METHODS: : Microcone beam CT images of nine healthy mice were contoured with an in-house developed multiatlas-based image segmentation (MABIS) algorithm for six OARs: kidneys, eyes, heart, and brain. The automatic contouring was compared with the manual delineation using three quantitative metrics: the Dice Similarity Coefficient (DSC), 95th percentile Hausdorff Distance, and the centre of mass displacement. RESULTS: : A good agreement between manual and automatic contouring was found for OARs with sharp organ boundaries. For the brain and the heart, the median DSC was larger than 0.94, the median 95th Hausdorff Distance smaller than 0.44 mm, and the median centre of mass displacement smaller than 0.20 mm. Lower DSC values were obtained for the other OARs, but the median DSC was still larger than 0.74 for the left eye, 0.69 for the right eye, 0.89 for the left kidney and 0.80 for the right kidney. CONCLUSION: : The MABIS algorithm was able to delineate six OARs with a relatively high accuracy. Segmenting OARs with sharp organ boundaries performed better than low contrast OARs. ADVANCES IN KNOWLEDGE:: A MABIS algorithm is developed, evaluated, and demonstrated in a preclinical small animal irradiation research workflow.
OBJECTIVE: : During the treatment planning of a preclinical small animal irradiation, which has time limitations for reasons of animal wellbeing and workflow efficiency, the time consuming organ at risk (OAR) delineation is performed manually. This work aimed to develop, demonstrate, and quantitatively evaluate an automated contouring method for six OARs in a preclinical irritation treatment workflow. METHODS: : Microcone beam CT images of nine healthy mice were contoured with an in-house developed multiatlas-based image segmentation (MABIS) algorithm for six OARs: kidneys, eyes, heart, and brain. The automatic contouring was compared with the manual delineation using three quantitative metrics: the Dice Similarity Coefficient (DSC), 95th percentile Hausdorff Distance, and the centre of mass displacement. RESULTS: : A good agreement between manual and automatic contouring was found for OARs with sharp organ boundaries. For the brain and the heart, the median DSC was larger than 0.94, the median 95th Hausdorff Distance smaller than 0.44 mm, and the median centre of mass displacement smaller than 0.20 mm. Lower DSC values were obtained for the other OARs, but the median DSC was still larger than 0.74 for the left eye, 0.69 for the right eye, 0.89 for the left kidney and 0.80 for the right kidney. CONCLUSION: : The MABIS algorithm was able to delineate six OARs with a relatively high accuracy. Segmenting OARs with sharp organ boundaries performed better than low contrast OARs. ADVANCES IN KNOWLEDGE:: A MABIS algorithm is developed, evaluated, and demonstrated in a preclinical small animal irradiation research workflow.
Authors: Alize E H Scheenstra; Rob C G van de Ven; Louise van der Weerd; Arn M J M van den Maagdenberg; Jouke Dijkstra; Johan H C Reiber Journal: Mol Imaging Date: 2009 Jan-Feb Impact factor: 4.488
Authors: Stefan Klein; Marius Staring; Keelin Murphy; Max A Viergever; Josien P W Pluim Journal: IEEE Trans Med Imaging Date: 2009-11-17 Impact factor: 10.048
Authors: Martin Baiker; Julien Milles; Jouke Dijkstra; Tobias D Henning; Axel W Weber; Ivo Que; Eric L Kaijzel; Clemens W G M Löwik; Johan H C Reiber; Boudewijn P F Lelieveldt Journal: Med Image Anal Date: 2010-05-21 Impact factor: 8.545
Authors: William P Segars; Benjamin M W Tsui; Eric C Frey; G Allan Johnson; Stuart S Berr Journal: Mol Imaging Biol Date: 2004 May-Jun Impact factor: 3.488