Knowledge-based interpretation of MR brain images
- 1 January 1996
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Medical Imaging
- Vol. 15 (4) , 443-452
- https://doi.org/10.1109/42.511748
Abstract
The authors have developed a method for fully automated segmentation and labeling of 17 neuroanatomic structures such as thalamus, caudate nucleus, ventricular system, etc. in magnetic resonance (MR) brain images. The authors' method is based on a hypothesize-and-verify principle and uses a genetic algorithm (GA) optimization technique to generate and evaluate image interpretation hypotheses in a feedback loop. The authors' method was trained in 20 individual T1-weighted MR images. Observer-defined contours of neuroanatomic structures were used as a priori knowledge. The method's performance was validated in eight MR images by comparison to observer-defined independent standards. The GA-based image interpretation method correctly interpreted neuroanatomic structures in all images from the test set. Computer-identified and observer-defined neuroanatomic structure areas correlated very well (r=0.99, y=0,95x-2.1). Border positioning errors were small, with a root mean square (rms) border positioning error of 1.5+/-0.6 pixels. The authors' GA-based image interpretation method represents a novel approach to image interpretation and has been shown to produce accurate labeling of neuroanatomic structures in a set of MR brain images.Keywords
This publication has 36 references indexed in Scilit:
- Integration of multiple knowledge sources in a system for brain CT-scan interpretation based on the blackboard modelPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain imagesIEEE Transactions on Medical Imaging, 1995
- A multispectral analysis of brain tissuesMagnetic Resonance in Medicine, 1993
- Image Processing, Analysis and Machine VisionPublished by Springer Nature ,1993
- Quantification of MR brain images by mixture density and partial volume modelingIEEE Transactions on Medical Imaging, 1993
- Knowledge-based classification and tissue labeling of MR images of human brainIEEE Transactions on Medical Imaging, 1993
- Unsupervised tissue type segmentation of 3D dual-echo MR head dataImage and Vision Computing, 1992
- Techniques for Cardiac Image SegmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- Computer-Based System for Quantitative Analysis of Physiological Structures from MRI DataJournal of Clinical Engineering, 1991
- Anatomic segmentation and volumetric calculations in nuclear magnetic resonance imagingIEEE Transactions on Medical Imaging, 1989