A Segmentation Method of Skin MRI 3D High Resolution in vivo
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Abstract
Background: In recent years, Magnetic Resonance Imaging (MRI) is used in clinical application as non-invasive medical modality, it is rarely used to study the anatomy physiological, and biochemical of the skin, in spite of its very attractive modality for skin imaging. It makes an ideal imaging modality of unique soft tissue contrast to study the skin water content and to differentiate between the different skin layers. However MRI provides a big data with high quality. The analysis of these data require computerized methods to help clinicians and to improve disease of diagnosis. Several image processing method have been extensively used to assist doctors in qualitative diagnosis, segmentation is one of the most methods used in medical image processing for many applications in order to understand medical data and extract useful information.
The purpose of this study is to use the segmentation method to measure the hydration of skin using MRI modality.
Methods: We will classify segmentation approaches for MRI data into three basics classes: Edge based segmentation, Region based segmentation, and Thresholding segmentation. Then we will briefly describe Fuzzy C-means Clustering method. Furthermore, we will give some related works used FCM algorithm with MRI images.
Results: We have measured the hydration of the feet as a result of the FCM segmentation method, where the sample of the study was conducted on 35 healthy volunteers, who were scanned by MRI machine before applying moisturizer and one hour after.
Conclusion: MRI is an attractive modality to study the skin water content, it makes an ideal observation of the different skin layers in vivo with three dimensions. However, the segmentation of MRI data by FCM clustering is a computerized method to help clinicians in order to measure skin hydration.
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