Segmentation Assisted Object Distinction for Direct Volume Rendering | ||
| Journal of AI and Data Mining | ||
| مقاله 7، دوره 8، شماره 1، فروردین 2020، صفحه 67-82 اصل مقاله (1.91 M) | ||
| نوع مقاله: Original/Review Paper | ||
| شناسه دیجیتال (DOI): 10.22044/jadm.2019.7207.1854 | ||
| نویسندگان | ||
| A. Azimzadeh Irani* ؛ R. Pourgholi | ||
| School of Mathematics and Computer Science, Damghan University, Damghan, Iran. | ||
| چکیده | ||
| Ray Casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a sufficiently powerful voxel parsing mechanism for object distinction. In this work, we are proposing an image processing based approach towards enhancing ray casting technique for object distinction process. The rendering mode is modified to accommodate masking information generated by a K-means based hybrid segmentation algorithm. An effective set of image processing techniques are creatively employed in construction of a generic segmentation system capable of generating object membership information. | ||
| کلیدواژهها | ||
| Hybrid image segmentation؛ Volume rendering؛ Enhanced visualization effect | ||
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آمار تعداد مشاهده مقاله: 604 تعداد دریافت فایل اصل مقاله: 610 |
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