Using Image Analysis and Visualization Technique in Tumor Diagnosis and Surgical Assist over the Craniofacial Area
Date Issued
2011
Date
2011
Author(s)
Mon-Hsian Hsieh, Thomas
Abstract
For years the medical image study has been a reliable and important tool for pre-operative diagnosis in the craniofacial surgery domain. With the improvement of the imaging instrument, and the progression of the computer hardware, now these imaging technique had went beyond simple visualization, the emerging of more complicated and advanced image analysis technique had extend the utility of image diagnosis.
To meet the specific and complex requirements of these biomedical image analyses, many researchers had devoted themselves in the development of the analyzing algorithm. Among them, algorithm used for isolating the meaningful component or pathology from the medical image, called image segmentation, had been studied intensively in recent years. However, most of the researches were focused on the neoplasm detection over intra-cranial space, and studies regarding the extensive neoplasm and hyperplasia over the extra-cranial and facial area were few. This may due to the its small case number and more variable clinical presentation, combined with more complicated anatomy make conclusive result more difficult in this area.
So, in this research, will try to develop a feasible algorithm and also a strategy to sucessfully isolated the neoplasm over the craniofacial area. The research comprised mainly two parts, at the first part we will introduce a multi-stage algorithm based on Fuzzy-c-mean technique for image segmentation of the intra-cranial tumor. On second part of our study, we’ll extend the use of this algorithm to more challenging extra-cranial lesion, that is, the benign neoplasm and hyperplasia over the craniofacial region. Due to more variable of the tumor location and the heterogeneous character of the tumor images, a more flexible and freely-used strategy is needed here for optimizing the result of image analysis for individual case. We’ll also introduce a visualization method that will properly demonstrate the results of these image analyses.
Finally we will present few clinical cases in order to the contribution of our research to clinical practice. We think these techniques could effectively help us in pre-operation diagnosis, surgical planning and post-operative follow-up. This technique could be easily interfaced with other Hi-tech instruments, and the potential for further development is promising.
Subjects
Craniofacial
Image segmentation
Region growing
Deformable model
Fuzzy-C-Mean
Knowledge-based
Multi-surface
Type
thesis
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