Automatic multiatlas based organ at risk segmentation in mice

Brent Van Der Heyden, Mark Podesta, Danielle B. P. Eekers, Ana Vaniqui, Isabel P. Almeida, Lotte E. J. R. Schyns, Stefan J. Van Hoof, Frank Verhaegen*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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.

Original languageEnglish
Article number20180364
Number of pages7
JournalBritish Journal of Radiology
Issue number1095
Publication statusPublished - 2019


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