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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
Year of Publication: 2021
Zainab Al-Rahamneh, Asma’a Khtoom, Mohammad Ryalat

Zainab Al-Rahamneh, Asma’a Khtoom and Mohammad Ryalat. Evaluation of Applying Surface Simplification Techniques in Medical Volume Data. International Journal of Computer Applications 183(9):7-11, June 2021. BibTeX

	author = {Zainab Al-Rahamneh and Asma’a Khtoom and Mohammad Ryalat},
	title = {Evaluation of Applying Surface Simplification Techniques in Medical Volume Data},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2021},
	volume = {183},
	number = {9},
	month = {Jun},
	year = {2021},
	issn = {0975-8887},
	pages = {7-11},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2021921423},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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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Medical Volume Data, Medical Images, Surface Simplification, Dice Coefficient, Stl Files