Multi-organ abdominal CT segmentation using hierarchically weighted subject-specific atlases

A robust automated segmentation of abdominal organs can be crucial for computer aided diagnosis and laparoscopic surgery assistance. Many existing methods are specialised to the segmentation of individual organs or struggle to deal with the variability of the shape and position of abdominal organs....

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Published inMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Vol. 15; no. Pt 1; p. 10
Main Authors Wolz, Robin, Chu, Chengwen, Misawa, Kazunari, Mori, Kensaku, Rueckert, Daniel
Format Journal Article
LanguageEnglish
Published Germany 2012
Subjects
Adult
Aged
Aged, 80 and over
Algorithms
Automation
Diagnostic Imaging - methods
Female
Humans
Kidney - pathology
Liver - pathology
Male
Middle Aged
Models, Anatomic
Models, Statistical
Models, Theoretical
Pancreas - pathology
Radiographic Image Interpretation, Computer-Assisted - methods
Radiography, Abdominal - methods
Reproducibility of Results
Spleen - pathology
Tomography, X-Ray Computed - methods
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Summary:A robust automated segmentation of abdominal organs can be crucial for computer aided diagnosis and laparoscopic surgery assistance. Many existing methods are specialised to the segmentation of individual organs or struggle to deal with the variability of the shape and position of abdominal organs. We present a general, fully-automated method for multi-organ segmentation of abdominal CT scans. The method is based on a hierarchical atlas registration and weighting scheme that generates target specific priors from an atlas database by combining aspects from multi-atlas registration and patch-based segmentation, two widely used methods in brain segmentation. This approach allows to deal with high inter-subject variation while being flexible enough to be applied to different organs. Our results on a dataset of 100 CT scans compare favourable to the state-of-the-art with Dice overlap values of 94%, 91%, 66% and 94% for liver, spleen, pancreas and kidney respectively.