Smoothing Module for Optimization Cranium Segmentation Using 3D Slicer

Gilang Argya Dyaksa(1*), Nur Arfian(2), Herianto Herianto(3), Lina Choridah(4), Yosef Agung Cahyanta(5),

(1) Faculty Science & Technology, Sanata Dharma University
(2) Department of Anatomy, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
(3) Department of Mechanical and Industrial Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia
(4) Department of Radiology, Faculty of Medicine, Public Health and Nursing, Yogyakarta, Indonesia
(5) Faculty Science & Technology, Sanata Dharma University
(*) Corresponding Author

Abstract


Anatomy is the most essential course in health and medical education to study parts of human body and also the function of it.  Cadaver is a media used by medical student to study anatomical subject. Because of limited access to cadaver and also due to high prices, this situation makes it necessary to develope an alternative anatomical education media, one of them is the use 3D printing to produce anatomical models. Before 3D Print the cranium, it is necessary to do the segmentation process and often the segmentation result is not good enough and appear a lot of noises. The purpose of this research is  to optimize a 3D cranium based on DICOM (digital imaging and communications in medicine) data processing using the smoothing modules on 3D Slicer. The method of this research is to process the Cranium DICOM data using 3D Slicer software by varying the 5 types of smoothing modules. The results with default parameter fill holes and median have better results compared to others. Kernel size variations are performed for smoothing module fill holes and medians. The result is fill holes get optimal segmentation results using a kernel size of 3 mm and the median is 5 mm

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References


K. Sugand, P. Abrahams, and A. Khurana, The anatomy of anatomy: A review for its modernization, Anat Sci Ed, (2010).

Biasutto SN et al., Human bodies to teach anatomy: importance and procurement—experience with cadaver donation, (2014).

M. M. Romi, N. Arfian, and D. C. R. Sari, Is Cadaver Still Needed in Medical Education?, JPKI, 8 (3) (2019) 105.

X. Zhang, K. Zhang, Q. Pan, and J. Chang, Three-dimensional reconstruction of medical images based on 3D slicer, J., complex., health sci., 2 (1) (2019) 1–12.

A. AlHadidi, L. H. Cevidanes, B. Paniagua, R. Cook, F. Festy, and D. Tyndall, 3D quantification of mandibular asymmetry using the SPHARM-PDM tool box, Int J CARS, 7 (2) (2012) 265–271.

Djoko Kuswanto and A. Tontowi, Development of Additive Manufacturing Methods for Reconstruction and Redesign Cranial Bone Defects in Indonesia, (2014).

A. Fedorov et al., 3D Slicer as an image computing platform for the Quantitative Imaging Network, Magnetic Resonance Imaging, 30 (9) (2012) 1323–1341.

G. A. Dyaksa, N. Arfian, and L. Choridah, Development of Cranium 3dimension-Puzzle Products Using 3D Printing, (2020).

C. Pinter, A. Lasso, and G. Fichtinger, Polymorph segmentation representation for medical image computing, Computer Methods and Programs in Biomedicine, 171 (2019) 19–26.




DOI: https://doi.org/10.24071/ijasst.v5i1.6300

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