Journal article
Registration and machine learning-based automated segmentation of subcortical and cerebellar brain structures
NeuroImage (Orlando, Fla.), Vol.39(1), pp.238-247
2008
DOI: 10.1016/j.neuroimage.2007.05.063
PMCID: PMC2253948
PMID: 17904870
Abstract
The large amount of imaging data collected in several ongoing multi-center studies requires automated methods to delineate brain structures of interest. We have previously reported on using artificial neural networks (ANN) to define subcortical brain structures. Here we present several automated segmentation methods using multidimensional registration. A direct comparison between template, probability, artificial neural network (ANN) and support vector machine (SVM)-based automated segmentation methods is presented. Three metrics for each segmentation method are reported in the delineation of subcortical and cerebellar brain regions. Results show that the machine learning methods outperform the template and probability-based methods. Utilization of these automated segmentation methods may be as reliable as manual raters and require no rater intervention.
Details
- Title: Subtitle
- Registration and machine learning-based automated segmentation of subcortical and cerebellar brain structures
- Creators
- Stephanie Powell - Department of Radiology, The University of Iowa, Iowa City, Iowa, 52242-1057, USAVincent A Magnotta - Department of Radiology, The University of Iowa, Iowa City, Iowa, 52242-1057, USAHans Johnson - Department of Psychiatry, The University of Iowa, Iowa City, Iowa, 52242-1057, USAVamsi K Jammalamadaka - Vital Images, Inc., Minnetonka, Minnesota, 55343-4414, USARonald Pierson - Department of Psychiatry, The University of Iowa, Iowa City, Iowa, 52242-1057, USANancy C Andreasen - Department of Psychiatry, The University of Iowa, Iowa City, Iowa, 52242-1057, USA
- Resource Type
- Journal article
- Publication Details
- NeuroImage (Orlando, Fla.), Vol.39(1), pp.238-247
- DOI
- 10.1016/j.neuroimage.2007.05.063
- PMID
- 17904870
- PMCID
- PMC2253948
- NLM abbreviation
- Neuroimage
- ISSN
- 1053-8119
- eISSN
- 1095-9572
- Publisher
- Elsevier Inc
- Language
- English
- Date published
- 2008
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Psychiatry; Iowa Neuroscience Institute
- Record Identifier
- 9984003403302771
Metrics
15 Record Views