MRI BRAIN IMAGE SEGMENTATION BASED ON SPATIALLY CONSTRAINED GAUSSIAN MIXTURE MODEL WITH REVERSIBLE JUMP MARKOV CHAIN MONTE CARLO ALGORITHM
One of the Gaussian Mixture Model (GMM) applications that is quite successful is in image segmentation. The GMM application assumes pixel independence so that it can make noise in the Region of Interest (ROI). To overcome this, a lot of research integrates spatial information into Markov Random Fiel...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/39586 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |