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All Journal Indonesian of Health Information Management Journal (INOHIM) Nusantara Hasana Journal Arcitech: Journal of Computer Science and Artificial Intelligence Proceeding of International Conference Health, Science And Technology (ICOHETECH) Prosiding Seminar Informasi Kesehatan Nasional
Sri Widodo
Universitas Duta Bangsa Surakarta
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology Nursing Public Health

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Journal : Indonesian of Health Information Management Journal (INOHIM)

 1 
Klasifikasi Kanker dan Artery pada Citra Computed Tomography Menggunakan Deep Learning Convolution Neural Network Sri Widodo
Indonesian of Health Information Management Journal (INOHIM) Vol 10, No 2 (2022): INOHIM
Publisher : Lembaga Penerbitan Universitas Esa Unggul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47007/inohim.v10i2.444

Abstract

AbstractDetection of lung cancer can significantly reduce the average death rate from lung cancer. Research on detection of lung cancer has been done. Most research on lung cancer detection always begins with image preprocessing, lung segmentation, lung candidate segmentation and lung cancer detection. These steps can cause the detection process to take a long time. The proposed research is to classify cancer and arterial images on CT-Scan using   Convolution Neural Network (CNN). This research consists of two main points. Starting with the process of determining the region of interest (ROI) from the image of cancer and artery. The second is cancer classification and artery using CNN deep learning. The accuracy obtained from testing is 95%.Keyword: CNN, CtScan, Deep Learning, Lung Cancer, ROI AbstrakDeteksi awal kanker paru dapat menurunkan rata-rata angka kematian akibat kanker paru secara signifikan. Penelitian tentang deteksi awal kanker paru sudah banyak dilakukan. Sebagian besar studi mengenai deteksi kanker paru pada CT-Scan selalu diawali dengan preprosesing citra, segmentasi paru, segmentasi kandidat paru dan deteksi kanker paru. Langkah-langkah tersebut dapat menyebabkan proses deteksi membutuhkan waktu yang lama. Penelitian yang dilakukan adalah melakukan klasifikasi kanker dan arteri pada gambar Computed Tomography menggunakan Convolution Neural Network (CNN). Penelitian ini terdiri dari dua hal pokok. Pertama adalah preprosesing  dari citra kanker dan artery.  Kedua adalah klasifikasi  kanker dan artery  menggunakan deep learning CNN. Akurasi tertinggi yang didapatkan dari ujicoba adalah 95%.Kata Kunci: CNN, CtScan, Deep Learning, Lung Cancer, ROI
Co-Authors Anik Sulistiyanti Antonius Suhartanto Indra Agung Yudistira Khofifah Nurul Sa’adah Maryatun Maryatun Mohammad Faizuddin Nur Rizka Rahmawati Nurhayati Yunita Wisda Tumarta Arif Yusfida Aulia Putri Zalizah Awang Long