1Department of Electrical and Computer Engineering, Universitas Syiah Kuala. Jl. Tgk. Syech Abdur Rauf No. 7 Kopelma Darussalam, Banda Aceh 23111, Indonesia
2Department of Intelligent System, Faculty of Engineering, University of Duisburg-Essen. Bismarckstrasse 90, Building BC, 4. Floor, Duisburg 47057, Germany
BibTex Citation Data :
@article{JTSISKOM14125, author = {Maya Fitria and Cosmin Adrian Morariu and Josef Pauli and Ramzi Adriman}, title = {Implementing a non-local means method to CTA data of aortic dissection}, journal = {Jurnal Teknologi dan Sistem Komputer}, volume = {9}, number = {3}, year = {2021}, keywords = {aortic dissection; noise reduction; non-local means, CT image, denoising method;}, 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.}, issn = {2338-0403}, pages = {174--179} doi = {10.14710/jtsiskom.2021.14125}, url = {https://jtsiskom.undip.ac.id/article/view/14125} }
Refworks Citation Data :
Article Metrics:
Last update:
Last update: 2024-10-14 03:51:12
Starting from 2021, the author(s) whose article is published in the JTSiskom journal attain the copyright for their article and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. By submitting the manuscript to JTSiskom, the author(s) agree with this policy. No special document approval is required.
The author(s) guarantee that:
The author(s) retain all rights to the published work, such as (but not limited to) the following rights:
Suppose the article was prepared jointly by more than one author. Each author submitting the manuscript warrants that all co-authors have given their permission to agree to copyright and license notices (agreements) on their behalf and notify co-authors of the terms of this policy. JTSiskom will not be held responsible for anything arising because of the writer's internal dispute. JTSiskom will only communicate with correspondence authors.
Authors should also understand that their articles (and any additional files, including data sets and analysis/computation data) will become publicly available once published. The license of published articles (and additional data) will be governed by a Creative Commons Attribution-ShareAlike 4.0 International License. JTSiskom allows users to copy, distribute, display and perform work under license. Users need to attribute the author(s) and JTSiskom to distribute works in journals and other publication media. Unless otherwise stated, the author(s) is a public entity as soon as the article is published.