Comparison Of Brain Tissue Classification Algorithms With The Use Of Multimodal Efficiency Measure
| Authors | |
|---|---|
| Year of publication | 2008 |
| Type | Article in Proceedings |
| Conference | Analysis of Biomedical Signals and Images - Proceedings of 19th Biennal International Eurasip Conference BIOSIGNAL 2008 |
| MU Faculty or unit | |
| Citation | |
| Field | Use of computers, robotics and its application |
| Keywords | computational neuroanatomy;image analysis;classification;segmentation |
| Description | A multimodal measure for comparison of efficiency of classification algorithms is proposed. The algorithms selected for brain tissue classification in 3-D MRI images are the well-known k-NN and k-means classifiers which were adapted to the image data in the common stereotaxic space. The efficiency measure combines Jaccard coefficient, modified Rand index and Connectivity coefficient. Results are presented in 3-D plots with the use of ellipsoids instead of frequently used 1-D plots or tables. |
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