Implementing a non-local means method to CTA data of aortic dissection

Jurnal Teknologi dan Sistem Komputer

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Title Implementing a non-local means method to CTA data of aortic dissection
 
Creator Fitria, Maya
Morariu, Cosmin Adrian
Pauli, Josef
Adriman, Ramzi
 
Subject aortic dissection; noise reduction; non-local means, CT image, denoising method;
 
Description 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.
 
Publisher Departemen Teknik Komputer, Fakultas Teknik, Universitas Diponegoro
 
Date 2021-07-31
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier https://jtsiskom.undip.ac.id/article/view/14125
10.14710/jtsiskom.2021.14125
 
Source Jurnal Teknologi dan Sistem Komputer; Volume 9, Issue 3, Year 2021 (July 2021); 174-179
Jurnal Teknologi dan Sistem Komputer; Volume 9, Issue 3, Year 2021 (July 2021); 174-179
2338-0403
 
Language eng
 
Relation https://jtsiskom.undip.ac.id/article/view/14125/12698
 
Rights Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
https://creativecommons.org/licenses/by-sa/4.0
 

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