Aryati Aryati
Dengue Study Group, Institute Of Tropical Disease, Universitas Airlangga, Mulyorejo Street, Mulyorejo 60115, Surabaya, East Java, Indonesia Clinical Pathology Department, Faculty Of Medicine, Universitas Airlangga, Prof.Dr.Moestopo Street, Tambaksari

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Journal : Bulletin of Electrical Engineering and Informatics

Multimodal deep learning from sputum image segmentation to classify Mycobacterium tuberculosis using IUATLD assessment Saurina, Nia; Chamidah, Nur; Rulaningtyas, Riries; Aryati, Aryati
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.9250

Abstract

Tuberculosis (TB) continues to be a major global health issue, especially in areas with limited resources where diagnostic tools are often insufficient. Traditional TB detection methods are slow and lack sensitivity, particularly for early-stage or low bacterial load cases. This study introduces a new multimodal deep learning model that integrates sputum image segmentation across RGB, hue, saturation, and value (HSV), and CIELAB color channels, using the YOLOv8 model for real-time detection and segmentation. The model uses the International Union Against Tuberculosis and Lung Disease (IUATLD) grading scale for accurate Mycobacterium tuberculosis (MTB) classification. Our approach shows high accuracy (92.24%) and precise forecasting (mean absolute percent error (MAPE) of 0.23%), greatly enhancing diagnostic speed and reliability. This research offers a novel method for classifying MTB using a multimodal deep learning model that integrates sputum image segmentation across RGB, HSV, and CIELAB color channels. By using the YOLOv8 model for real-time bounding box detection and segmentation, and the IUATLD grading scale for classification, our method achieves high accuracy and precision in identifying TB bacteria. Our findings indicate that this multimodal deep learning approach significantly improves diagnostic accuracy and speed, providing a reliable tool for early TB detection.
Co-Authors Agus Santosa Agus Sulistyono Agustin Iskandar Aksono HP., Eduardus Bimo Alida Roswita Harahap Anak Agung Wiradewi Lestari Andina Putri Aulia Andyanita Hanif Hermawati Anniwati, Leonita Aprilia, Andrea AR, M. Yazid Ariani, Grace Arifoel Hajat Bastiana Bastiana Budi Utomo Cavalier, Etienne Darto Saharso Desak Gde Ushadi Bulan Dewata Dewi Wulandari Djoko Santoso Doddy M. Soebadi Dominicus Husada Dwiyanti Puspitasari, Dwiyanti Eko Sulistijono Erawati Erawati Erni Juwita Nelwan, Erni Juwita Erwin Astha Triyono Fahimah Martak Ferdy Royland Marpaung Gondo Mastutik Handayani, Cut Fitri Harianto Notopuro Harsasi Setyawati Haryanto, Isnaeni Yudi Hebert Adrianto Heny Arwati Herdiman Theodorus Pohan Hermawati, Andayanita Hanif Hermina Novida, Hermina I A Putri Wirawati I Dewa Gede Ugrasena Ilham Harlan Amarullah Indah Susanti Iris Rengganis Isnaeni Isnaeni Yudi Haryanto Isnin Anang Marhana Jusak Nugraha Kris Cahyo Mulyatno, Kris Cahyo Kuntaman Kuntaman Kusmiati, Tutik Kusumastuti, Etty H. Laksita, Tetuka B. Lulut Kusumawati Lumban Toruan, Anggia Augustasia M. Andriady S. Nasution Maharani, Anisa Mardiyah, Nikmatul Margalin, Brilliant Marpaung, Ferdy Royland Masanori Kameoka, Masanori Masyeni, Sri Ma`ruf, Anwar Merylin Ranoko Mohammad Guritno Suryokusumo Mufasirin Muhammad Nazarudin Muhammad Rivai Mustika Amri Nabil Salim Ambar Nia Saurina Niluh Suwasanti Norwahyuni, Yuyun Nunki, Nastasya Nur Chamidah Nurdianto, Arif Rahman Patria Dewi, Pande Putu Ayu Perbowo, Primandono Pranidya, Nada Putri Purnomo, Windu Puspa Wardhani R Raharjo, Paulus R. Tedjo Sasmono Rahmawati, Lita Diah Retno Palupi Riries Rulaningtyas Rizaliansyah, Ferdian Rizqidhana Juliana Putri Rony, Zahara Tussoleha Royland Marpaung, Ferdy Rusli, Musofa Saptawati Bardosono Saraswati Dewi Sari, Arabella Vonia Sasmono, R. Tedjo Setianingsih, Yennie A. Shifa Fauziyah Shuhai Ueda Siti Churrotin, Siti Soegeng Soegijanto Sofro, Muchlis AU Sri Subekti Sri Sumarsih Suci Andriani Suhendro Suhendro SUKACITA TEHUPURING Sunari, I Gusti Agung Ayu Eka Putri Sunaryo Hardjowijoto Suprapto Maat Teguh Hari Sucipto, Teguh Hari Theresia Indah Budhy Sulisetyawati Thomas Tandi Manu Tjokroprawiro, Brahmana A. Tomohiro Kotaki, Tomohiro Trieva Verawaty Butarbutar Ueda, Shuhai Usman Hadi wahjoe djatisoesanto Wardhani, Puspa Wibrianto, Aswandi Widajati, Rahma Widodo J Pujiraharjo Yetti Hernaningsih Yohan, Benediktus Yovilianda Maulitiva Untoro Yulia Iriani, Yulia Yulia Nadar Indrasari Yuliasih