Title
A multi-object statistical atlas adaptive for deformable registration errors in anomalous medical image segmentation.
Abstract
Statistical Atlases have played an important role towards automated medical image segmentation. However, a challenge has been to make the atlas more adaptable to possible errors in deformable registration of anomalous images, given that the body structures of interest for segmentation might present significant differences in shape and texture. Recently, deformable registration errors have been accounted by a method that locally translates the statistical atlas over the test image, after registration, and evaluates candidate objects from a delineation algorithm in order to choose the best one as final segmentation. In this paper, we improve its delineation algorithm and extend the model to be a multi-object statistical atlas, built from control images and adaptable to anomalous images, by incorporating a texture classifier. In order to provide a first proof of concept, we instantiate the new method for segmenting, object-by-object and all objects simultaneously, the left and right brain hemispheres, and the cerebellum, without the brainstem, and evaluate it on MRT1-images of epilepsy patients before and after brain surgery, which removed portions of the temporal lobe. The results show efficiency gain with statistically significant higher accuracy, using the mean Average Symmetric Surface Distance, with respect to the original approach.
Year
DOI
Venue
2017
10.1117/12.2254477
Proceedings of SPIE
Keywords
Field
DocType
Adaptive probabilistic atlas,pathological MR-images of the brain,anomalous medical image segmentation
Computer vision,Market segmentation,Scale-space segmentation,Segmentation,Computer science,Image segmentation,Proof of concept,Atlas (anatomy),Artificial intelligence,Classifier (linguistics),Standard test image
Conference
Volume
ISSN
Citations 
10133
0277-786X
0
PageRank 
References 
Authors
0.34
8
4
Name
Order
Citations
PageRank
Samuel Botter Martins121.04
Thiago Vallin Spina2457.32
Clarissa Lin Yasuda343.55
Alexandre X. Falcão41877132.30