{"id":16442,"date":"2025-10-14T14:07:53","date_gmt":"2025-10-14T07:07:53","guid":{"rendered":"https:\/\/fkg.ugm.ac.id\/?p=16442"},"modified":"2025-12-01T14:16:39","modified_gmt":"2025-12-01T07:16:39","slug":"penggunaan-teknologi-diagnostik-untuk-penyakit-mulut","status":"publish","type":"post","link":"https:\/\/fkg.ugm.ac.id\/en\/penggunaan-teknologi-diagnostik-untuk-penyakit-mulut\/","title":{"rendered":"The Use of Diagnostic Technology for Oral Diseases"},"content":{"rendered":"

Oral diseases such as oral cancer, precancerous lesions, infections, and oral tissue disorders remain serious challenges in dentistry and public health. These conditions are often detected at an advanced stage because early symptoms are difficult to recognise. Therefore, innovative diagnostic technologies are critically important for early, rapid, and non-invasive screening.<\/p>\n\n\n\n

One of the latest innovations comes from the UGM Student Creativity Program \u2013 Product Development (PKM-KC) Research Team, consisting of Heironymus Damar Jati Danisworo, Aurelius Galih Arkananta, Hikmat Sejati, and Fatimah Islamia, who developed a rapid detection device for oral cancer called Orside: A Portable Fluorescence-Based Precancerous Lesion Detector with Deep Learning Convolutional Neural Network (CNN). This device is designed to detect abnormal oral lesions more quickly and accurately at the point of care.\u00a0<\/p>\n\n\n\n

Modern Diagnostic Technologies in Oral Diseases<\/strong><\/h2>\n\n\n\n

Several advanced diagnostic approaches and technologies currently used or under development in the field of oral diseases include:<\/p>\n\n\n\n

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  1. Optical Fluorescence and Autoluminescence<\/strong>
    This method utilises the different properties of healthy and abnormal tissues in emitting or absorbing light at specific wavelengths. The Orside device uses blue fluorescence light to differentiate between healthy and abnormal tissues in the oral cavity.\u00a0<\/li>\n\n\n\n
  2. Artificial Intelligence (AI) \/ Deep Learning \/ CNN<\/strong>
    Images obtained from scanning are processed using deep learning algorithms (CNN) to recognise micro-patterns that are not visible to the human eye. Orside applies CNN for image analysis and prediction of precancerous lesions based on fluorescence results.\u00a0<\/li>\n\n\n\n
  3. Multimodal Imaging (Optical + Spectroscopy)<\/strong>
    The combination of techniques such as fluorescence, spectroscopy, and optical reflectance can provide additional information on tissue biochemical content, helping to distinguish normal from pathological tissues.<\/li>\n\n\n\n
  4. 3D Imaging and Cone Beam \/ CT \/ CBCT Imaging<\/strong>
    For the diagnosis of structural abnormalities, tumors, and surgical planning, CBCT and CT technologies are used to accurately visualise bone structures and hard\/soft tissues of the oral cavity.<\/li>\n\n\n\n
  5. Mobile Imaging \/ Tele-diagnosis \/ Smartphone Applications<\/strong>
    The use of smartphone cameras with special lenses, supported by AI algorithms, enables patients or primary healthcare providers to perform initial self-screening or screening in basic healthcare facilities.<\/li>\n<\/ol>\n\n\n\n

    Advantages and Benefits of Diagnostic Technologies Such as Orside<\/strong><\/h2>\n\n\n\n