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Politeknik Elektronika Negeri Surabaya
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Tuberculosis Detection based on Lung X-Ray Images Using Convolutional Neural Networks (CNN) Kurniawan, Rudi; Badriyah, Tessy; Syarif, Iwan
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER Vol 7 No 1 (2024): June
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/atcsj.v7i1.6448

Abstract

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis, primarily affecting the lungs. Despite being preventable and curable, TB remains a significant global health issue, especially in developing countries. The success of TB treatment heavily depends on the accuracy of the diagnosis, which typically requires expertise from pulmonology or radiology specialists to interpret chest X-ray images.  This study aims to design an assistive tool for TB detection that can automatically diagnose the disease using chest X-ray data.  The study implemented a Convolutional Neural Network (CNN) architecture to analyze the X-ray images. Additionally, image preprocessing and early stopping methods were employed to enhance accuracy performance, optimize computation, and prevent overfitting.  Experiment was conducting using 75% of the data as training data to generate the model and then applied to 25% of the data as testing data. This study comparing image sizes in RGB and grayscale modes. Experimental results show that the use of early stopping has a significant impact on training time, reducing training time substantially in almost all scenarios without drastically sacrificing accuracy. Without early stopping, accuracy does tend to be higher, as seen in grayscale color mode with an image size of 128x128, where the accuracy reaches 0.992, and in RGB mode with an image size of 64x64 which reaches 0.995. However, training time also increases significantly, for example for a 299x299 image with RGB mode, the training time reaches 927 seconds. Therefore, while RGB yields slightly higher accuracy, grayscale is recommended due to significantly faster training times. Additionally, the early stopping mechanism proves effective in reducing computational time, making the training process more efficient.
Co-Authors Achmad Thorikul Huda Adam Ghazy Al Falah Adam Prugel-Bennett Agung Muliawan Ahmad Syauqi Ahsan Ahsan, Ahmad Syauqi Aidil Saputra Kirsan Aidil Saputra Kirsan Aji , Rendra Suprobo Al Falah, Adam Ghazy Alfaqih, Wildan Maulana Akbar Ali Ridho Barakbah Alwan Fauzi Amalia Wirdatul Hidayah Andhik Ampuh Yunanto APRIANDY, KEVIN ILHAM Ardhani, Misbahul Arna Fariza Assodiky, Hilmy Assodiky, Hilmy Asy Syaffa Khoirunnisa Ayu Ahadi Ningrum Aziz, Adam Shidqul Bagas Dewangkara Bima Sena Bayu Dewantara Binti Kholifah Dadet Pramadihanto Daisy Rahmania Syarif Darmawan, Zakha Maisat Eka Desy Intan Permatasari Desy Intan Permatasari, Desy Intan Deyana Kusuma Wardani Dian Neipa Purnamasari Dimas Bagus Santoso Dona Wahyudi Dzulfiqar, Achmad Fakhri Edelani, Renovita Edi Satriyanto Entin Martiana Kusumaningtyas Fahrudin, Tresna Maulana Fahrudin, Tresna Maulana Fakhri, Haidar Fathoni, Kholid Fauzy, Aryazaky Iman Ferry Astika Saputra Ferry Astika Saputra Ferry Astika Saputra Fitri Setyorini Gary Wills Grezio Arifiyan Primajaya Gunawan, Agus Indra Hardiyanti, Fitriani Rohmah Hasan Basri Hidayah, Amalia Wirdatul Hidayah, Nadila Wirdatul Hisyam, Masfu Hisyam, Masfu Idris Winarno Izza Nur Afifah Khoirunnisa, Asy Syaffa Kholifah, Binti Kindarya, Fabyan Kusuma, Harun Indra Kusuma, Selvia Ferdiana M Udin Harun Al Rasyid, M Udin Harun Mahardhika, Yesta Medya Maulana, Yufri Isnaini Rochmat Maulana, Yufri Isnaini Rochmat Mayangsari, Mustika Kurnia Mufid, Mohammad Robihul Mufid, Mohammad Robihul Muhammad Fajrul Falah Muhlis Tahir Nadila Wirdatul Hidayah Nana Ramadijanti Nana Ramadijanti, Nana Novie Ayub Windarko Nur Rosyid Mubtadai Nur Rosyid Mubtadai, Nur Rosyid Nur Sakinah Nur Ulima Rusmayani Oktavia Citra Resmi Rachmawati Osamah Abdullah Yahya Amran Prasetyo Primajaya, Grezio Arifiyan Puspasari Susanti Rabiatul Adawiyah Reesa Akbar Rengga Asmara Rengga Asmara Renovita Edelani Riyanto Sigit, Riyanto Rizky Yuniar Hakkun Rosmaliati, Rosmaliati Rozie, Fachrul Rudi Kurniawan Rudi Kurniawan Rulisiana Widodo S, Ferry Astika S, Ferry Astika Sa'adah, Umi Selvia Ferdiana Kusuma Setiawardhana Setiawardhana Setiawardhana, Setiawardhana Shabirin, Irsal Silfiana Nur Hamida Sritrusta Sukaridhoto Sudaryanto, Aris Sumarsono, Irwan Tahir, Muhlis Tessy Badriyah, Tessy Tri Harsono Ubed, Imanullah Ali Umi Sa'adah Utomo, Agus Priyo Wahjoe Tjatur Sesulihatien Walujo, Ivana Yudith Wibowo, Prasetyo Willy Sandhika