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Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems)
Article . 2014
Data sources: DOAJ
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Sistem Diagnosis Kanker Servik Berdasarkan Karakteristik Morfologi

descriptionPublicationkeyboard_double_arrow_right Article 01 Mar 2014 English Publisher:Departement of Electrical Engineering, Faculty of Engineering, Universitas BrawijayaJournal:Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) (issn: 2460-8122, Copyright policy )
Authors: Rahmadwati Rahmadwati;

Sistem Diagnosis Kanker Servik Berdasarkan Karakteristik Morfologi

Abstract

Penelitian ini mengkaji diagnosis kanker serviks berdasarkan karakteristik morfologi sel serviks. Algoritma yang dikembangkan meliputi beberapa langkah: pra-pengolahan, segmentasi citra, inti dan sitoplasma deteksi, perhitungan fitur, dan klasifikasi. Algoritma K-means clustering berdasarkan segmentasi warna digunakan untuk memisahkan citra biopsi serviks menjadi empat daerah: latar belakang, inti sel, stroma dan sitoplasma. Karakteristik morfologi sel serviks digunakan untuk ekstraksi fitur gambar histologi serviks. Berdasarkan empat fitur diskriminatif: 1) rasio inti ke sitoplasma, 2) diameter inti, 3) faktor bentuk dan 4) pleiomorphic inti gambar histologi serviks diklasifikasikan. Kemudian citra dianalisis dan diklasifikasikan ke dalam kelas yang sesuai. Metode ini digunakan untuk mengklasifikasikan citra kanker serviks menjadi normal, kanker pra dan ganas. Kata Kunci—diagnosis, kanker servik, karakteristik, morfologi

Keywords

TK4001-4102, TK7800-8360, Applications of electric power, Electronics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold