دورية أكاديمية
Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images
| العنوان: | Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images |
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| المؤلفون: | Ng, SK, McLachlan, GJ |
| بيانات النشر: | Pergamon |
| سنة النشر: | 2004 |
| المجموعة: | Griffith University: Griffith Research Online |
| مصطلحات موضوعية: | Information systems, Other information and computing sciences not elsewhere classified |
| الوصف: | Mixture models implemented via the expectation-maximization (EM) algorithm are being increasingly used in a wide range of problems in pattern recognition such as image segmentation. However, the EM algorithm requires considerable computational time in its application to huge data sets such as a three-dimensional magnetic resonance (MR) image of over 10 million voxels. Recently, it was shown that a sparse, incremental version of the EM algorithm could improve its rate of convergence. In this paper, we show how this modified EM algorithm can be speeded up further by adopting a multiresolution kd-tree structure in performing the E-step. The proposed algorithm outperforms some other variants of the EM algorithm for segmenting MR images of the human brain. ; No Full Text |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 0031-3203 |
| العلاقة: | Pattern Recognition; http://hdl.handle.net/10072/33488Test |
| DOI: | 10.1016/j.patcog.2004.02.012 |
| الإتاحة: | https://doi.org/10.1016/j.patcog.2004.02.012Test http://hdl.handle.net/10072/33488Test |
| رقم الانضمام: | edsbas.C4DB94D |
| قاعدة البيانات: | BASE |
| تدمد: | 00313203 |
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| DOI: | 10.1016/j.patcog.2004.02.012 |