Algoritma Genetika untuk Deteksi Tumor

Article Sidebar

PDF
Published: May 31, 2021
DOI: https://doi.org/10.52005/fidelity.v3i2.93
(Abstract view) : 269
(PDF download) : 237
Keywords:
Deteksi tumor, pengelompokan, algoritma genetika

Main Article Content

Didha Prayoga
R&D PT. Len Railway Systems Jakarta

Abstract

Dalam dunia medis, deteksi tumor adalah tugas yang kritis dan menantang. Makalah ini memberikan gambaran tentang pemanfaatan algoritma genetika untuk mendeteksi tumor pada foto medis. Citra otak diperoleh dari database pasien pada tahap pertama. Clustering dan algoritma genetika dengan beberapa tahapan digunakan pada langkah selanjutnya. Operasi genetik yang dilakukan pada citra cluster untuk mendapatkan hasil yang dibutuhkan meliputi seleksi, crossover, dan mutasi. Algoritma genetik untuk gambar otak dijelaskan dalam penelitian ini. Kumpulan foto tumor otak populasi awal sangat banyak. Namun, pengelompokan dan genetika meminimalkan kumpulan populasi ini. Setelah daerah ini telah ditentukan, digunakan sebagai set populasi genetik. Di bidang ini, genetika sedang digunakan, dan deteksi tumor menjadi semakin berhasil.

Article Details

How to Cite
[1]
D. Prayoga, “Algoritma Genetika untuk Deteksi Tumor”, Fidelity, vol. 3, no. 2, pp. 32-35, May 2021.
Issue
Vol 3 No 2 (2021): Edition for May 2021
Section
Articles

Lisensi Creative Commons
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish with FIDELITY : Jurnal Teknik Elektro agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal. 
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.

Lisensi Creative Commons
Jurnal FIDELITY : Jurnal Teknik Elektro is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Received 2021-03-11
Accepted 2021-04-21
Published 2021-05-31

References

Banzhaf, Wolfgang, Nordin,Peter Keller, Robert FranconeFrank,"Genetic Programming: An Introduction, Morgan Kaufmann, an Francisco,CA,1998.

J.H. Holland (2005) Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, Michigan; re-issued by MIT Press (2003).

Garima Garg and Sonia Juneja "Brain Tumor Segmentation using Genetic Algorithm and FCM Clustering Approach". International Journal of Computer Applications 49(2):22/27, July 2012, Foundation of Computer Science, New Delhi.

A .R. Fallahi, M. Pooyan and H. Khotanlou (2010). A New Approach For Classification of Human Brain CT Images Based on Morphological Operations, Journal of Biomedical Science and Engineering, vol. 3, pp. 78-82.

D.E.Goldberg(2009) Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, Massachusetts.

T. Logeswari, M Karan (2010). An Enhanced Implementation of Brain Tumor Detection Using Segmentation Based on Soft Computing. Signal Acquisition and Processing, 2010. ICSAP '10. International Conference on 9-10 Feb. 2010, pp: 243 – 247, E-ISBN: 978-1- 4244-5725-0, Bangalore.

Lorenzen P., Joshi S., Gerig G., and Bullitt E (2001)"Tumor-Induced Structural and Rometric Asymmetry in Brain images". Proc the IEEE workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA), vol.1, pp: 488-501.

Fritz A. (2000). Classification of diseases for oncology. International World Health Organization, Geneva.

N.Nandha Gopal. (2010). Dr. M. Karnan, "Diagnose Brain Tumor Through MRI Using Image Processing Clustering Algorithms Such As Fuzzy C Means Along With Intelligent Optimization Techniques", 978-1-4244- 5967-4/10©2010 IEEE.