White matter hyper-intensities automatic identification and segmentation in magnetic resonance images
| Autor: | Lizette Johanna Patino-Correa, Oleksiy Pogrebnyak, Jesus Alberto Martinez-Castro, Edgardo M. Felipe-Riveron |
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| Rok vydání: | 2014 |
| Předmět: |
medicine.diagnostic_test
business.industry Computer science General Engineering Magnetic resonance imaging Image processing Image segmentation Grey matter Hyperintensity Computer Science Applications White matter medicine.anatomical_structure Artificial Intelligence medicine Computer vision Segmentation Artificial intelligence business |
| Zdroj: | Expert Systems with Applications. 41:7114-7123 |
| ISSN: | 0957-4174 |
| Popis: | A methodology for automatic identification and segmentation of white matter hyper-intensities appearing in magnetic resonance images of brain axial cuts is presented. To this end, a sequence of image processing technics is employed to form an image where the hyper-intensities in white matter differ notoriously from the rest of the objects. This pre-processing stage facilitates the posterior process of identification and segmentation of the hyper-intensity volumes. The proposed methodology was tested on 55 magnetic resonance images from six patients. These images were analysed by the proposed system and the resulted hyper-intensity images were compared with the images manually segmented by experts. The experimental results show the mean rate of true positives of 0.9, the mean rate of false positives of 0.7 and the similarity index of 0.7; it is worth commenting that the false positives are found mostly within the grey matter not causing problems in early diagnosis. The proposed methodology for magnetic resonance image processing and analysis may be useful in the early detection of white matter lesions. |
| Databáze: | OpenAIRE |
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