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All Journal Jurnal Buana Informatika Bulletin of Electrical Engineering and Informatics Disease Prevention and Public Health Journal Jurnal Teknik Sipil dan Perencanaan Scan : Jurnal Teknologi Informasi dan Komunikasi JPM17: Jurnal Pengabdian Masyarakat Journal of Information Systems Engineering and Business Intelligence Jurnal IPTEK INTEGER: Journal of Information Technology Didaktis: Jurnal Pendidikan dan Ilmu Pengetahuan SMARTICS Journal Jurnal Sains dan Informatika IJEBD (International Journal Of Entrepreneurship And Business Development) ILKOM Jurnal Ilmiah JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) JUTEKIN (Jurnal Manajemen Informatika) INTEK: Informatika dan Teknologi Informasi Adimas : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat IPTEKS JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Jurnal Manajemen Teknologi dan Teknik Sipil (JURMATEKS) Jurnal Pengabdian Masyarakat Asia Jurnal Terapan Manajemen dan Bisnis DECODE: Jurnal Pendidikan Teknologi Informasi Melek IT: Information Technology Journal Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem Informasi Dan E-Bisnis Research Horizon Jurnal Teknik Sipil PENITI BANGSA (Pemanfaatan Ilmu Pengetahuan dan Teknologi bagi Masyarakat)
Nia Saurina
Universitas Wijaya Kusuma Surabaya
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Journal : Bulletin of Electrical Engineering and Informatics

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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 AA Sudharmawan, AA adisusilo, Anang kukuh AGASTA, BAGAS RIFALDHI PUTRA Agung Wijanarko, Agung agus dwi rizal, agus dwi Akbar Bayu Kresno Suharso Alfandi, Ridho Allen Donouval Sahertian, Allen Donouval Amalia, Baiq Rizky Anang Adisusilo Anang Kukuh Adisusilo andari sinta dewi, andari sinta Andaryati Andaryati Andaryati, Andaryati arabigh, mochammad habib Ario Yusuf Christian Aryati Aryati auzan, Agi jabal tarig Bakhrul Na'im Irawan benny nasution, benny Brian Andreas Sutarto Brian Andreas Sutarto, Brian Andreas Che Zalina Zulkifli Christian, ario yusuf Citrawati Jatiningrum cristtian novianto, cristtian Dedy Setiawan Desi Rully Wahyuni Emmy Wahyuningtyas Erfan Rachmad Santosa, Erfan Rachmad Firman Hadi Firman Hadi S Pratama, Firman Hadi S Firman Hadi S.P Firman Hadi Sukma Pratama Firman Hadi Sukma Wijaya Firman Pratama guendra kusuma wardhana, guendra kusuma Hadi, Firman Hala Nuari Lina Darmayanti, Hala Nuari Lina Hasbullah . ., Hasbullah . Husein, Moch Idris, Azlina Ihsan Pribadi, Teguh Ikhsan, Teguh Pribadi Irawan, Bakhrul Na'im Iva Evry Robiyansah Jayanto, Denny Nur Karyanto, Nonot Wisnu Karyanto, Nonot Wisnu Lathifah Nur Karimah Lestari Retnawati lestari retnawati Luhulima, Stella Joice Lusy Tunik Muharlisiani M. Agi Jabal Tariq Auzan Mareta, Ninin Marina Revitriani Marina Revitriani Maslihah Maslihah Mochammad Habib Arabigh Nasution, Beny Y. V. Nia Saurina Ninin Mareta Nirmansyah, Suhardik Nonot Wisnu Karyanto Nonot Wisnu Karyanto Nonot Wisnu Karyanto, Nonot Noven Indra Prasetya novy yanto, novy Nur Chamidah Pratama, Firman Hadi S Pratiwi Dwi Karyati Pudjianto, Udik Pudjianto, Udik Purwaningrum, Sri Wulan Putra, Eka Prasetya rachmad hariyadi, rachmad Radi Radi retnawati, lestari Retnawati, Lestari RIFALDHIPUTRA AGASTA, BAGAS Rini, Titien Setiyo Riries Rulaningtyas Septian Roselina Dwi Ariani Septian Roselina Dwi Ariani, Septian Roselina Dwi Shofiya Syidada Shofiya Syidada Siswoyo Siswoyo Soepriyono, Soepriyono Suhardik Nirmansyah syamrama, ligar tara braja, tara Tawaqal Teguh Abid permadi Tjatursari Widiartin Udik Pudjianto Udik Pudjianto udik pudjianto Udik Pudjianto Wahyuni, Desi Rully Waskito, Johan Paing Heru Wijaya, Firman Hadi S wira lamba, wira Wisnu Yudo Untoro Wisnujatia, Nugrahini Susantinah