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https://hdl.handle.net/20.500.13091/1697
Title: | Thermogram classification using deep siamese network for neonatal disease detection with limited data | Authors: | Ervural, Saim Ceylan, Murat |
Keywords: | Disease Classification Neonatal Intensive Care One-Shot Learning Siamese Neural Network Thermal Imaging Low-Birth-Weight Infrared Thermography Natural-History System Thermoregulation Anomalies Infants |
Publisher: | Taylor & Francis Ltd | Abstract: | Monitoring the body temperatures and evaluating the thermal asymmetry of newborns give an idea about neonatal diseases. Infrared thermography is a non-invasive, non-harmful, and non-contact modality that allows the monitoring of the body temperature distribution. Early diagnosis using a limited data set is extremely vital due to the high mortality rate in newborns and some difficulties in neonatal imaging. Thermography stands out as a useful tool in detecting neonatal diseases compared to other techniques. However, creating a thermogram database consisting of thousands of images from each class required by traditional artificial intelligence methods, is impossible due to the sensitivity of newborns. One of the meta-learning models that has recently gained success in applying limited data learning, especially one-shot, in various fields is Siamese neural networks. In this work, we perform a multi-class classification to provide pre-diagnosis to experts in disease detection using Siamese neural networks. By using two different optimisation techniques and data augmentation, critical diseases with only a few sample data are classified using the method tested in two- and three-class evaluation approaches. The results based on the disease type achieve 99.4% accuracy in infection diseases and 96.4% oesophageal atresia, 97.4% in intestinal atresia, and 94.02% in necrotising enterocolitis. | URI: | https://doi.org/10.1080/17686733.2021.2010379 https://hdl.handle.net/20.500.13091/1697 |
ISSN: | 1768-6733 2116-7176 |
Appears in Collections: | Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
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Thermogram classification using deep siamese network for neonatal disease detection with limited data.pdf Until 2030-01-01 | 3.32 MB | Adobe PDF | View/Open Request a copy |
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