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All Journal Jurnal Teknologi dan Sistem Komputer
Josef Pauli
Department of Intelligent System, Faculty of Engineering, University of Duisburg-Essen. Bismarckstrasse 90, Building BC, 4. Floor, Duisburg 47057|University of Duisburg-Essen
Computer Science & IT Electrical & Electronics Engineering

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Implementing a non-local means method to CTA data of aortic dissection Maya Fitria; Cosmin Adrian Morariu; Josef Pauli; Ramzi Adriman
Jurnal Teknologi dan Sistem Komputer Volume 9, Issue 3, Year 2021 (July 2021)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2021.14125

Abstract

It is necessary to conserve important information, like edges, details, and textures, in CT aortic dissection images, as this helps the radiologist examine and diagnose the disease. Hence, a less noisy image is required to support medical experts in performing better diagnoses. In this work, the non-local means (NLM) method is conducted to minimize the noise in CT images of aortic dissection patients as a preprocessing step to produce accurate aortic segmentation results. The method is implemented in an existing segmentation system using six different kernel functions, and the evaluation is done by assessing DSC, precision, and recall of segmentation results. Furthermore, the visual quality of denoised images is also taken into account to be determined. Besides, a comparative analysis between NLM and other denoising methods is done in this experiment. The results showed that NLM yields encouraging segmentation results, even though the visualization of denoised images is unacceptable. Applying the NLM algorithm with the flat function provides the highest DSC, precision, and recall values of 0.937101, 0.954835, and 0.920517 consecutively.
Co-Authors Adriman, Ramzi Cosmin Adrian Morariu Maya Fitria