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Evaluation of Applying Surface Simplification Techniques in Medical Volume Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 9 |
| Year of Publication: 2021 |
| Authors: Zainab Al-Rahamneh, Asma’a Khtoom, Mohammad Ryalat |
10.5120/ijca2021921423
|
Zainab Al-Rahamneh, Asma’a Khtoom, Mohammad Ryalat . Evaluation of Applying Surface Simplification Techniques in Medical Volume Data. International Journal of Computer Applications. 183, 9 ( Jun 2021), 7-11. DOI=10.5120/ijca2021921423
Abstract
Medical volume data such as MRI and CT images consist of a large number of voxels. Thus, the process of displaying, storing and transmission of medical volume data is a big challenge in the biomedical field. Applying surface simplification techniques to reduce the size occupied by medical images is considered as one of the most common approachs to overcome this challenge. However, not all of the surface simplification techniques are accurate enough to be used in the medical fields. This paper aims to evaluate the impact and the accuracy of applying the Uniform Mesh Resampling (UMR) technique and the Quadric Edge Collapse Decimation (QECD) technique. Moreover, this study investigates Poisson Surface Reconstruction (PSR) technique and sets experimentally the optimal offsetting value of this technique. Two real medical benchmark datasets are used in this study to evaluate the experimental work. The outcomes indicate clearly that the use of QECD as a surface simplification technique achieves competitive results when used with medical volume data.
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