Deep Computer Based Pre-Diagnosis From Chest CTs of COVID-19 Patients
Yazarlar (1)
Doç. Dr. Ali Berkan URAL Kafkas Üniversitesi, Türkiye
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| DOI Numarası | 10.23919/ELECO54474.2021.9677723 | ||
| Kongre Adı | ELECO 2021 | ||
| Kongre Tarihi | 25-11-2021 / 27-11-2021 | ||
| Basıldığı Ülke | Türkiye | Basıldığı Şehir | Bursa |
| Bildiri Linki | https://ieeexplore.ieee.org/document/9677723/authors | ||
| UAK Araştırma Alanları |
Yapay Zeka
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| Özet |
| This study conducts a successful approach on Computer Aided Diagnosis area with using Image processing methods, optimized version of Artificial Neural Network (ANN) with Levenberg Marquardt (LM) algorithm, Deep Learning models (CNN based AlexNet, ResNet-50 and optimized version of CNN with GA). Totally, 1000 patients with COVID-19 (%50 of male and %50 of female), including %50 of severe and %50 of moderate cases and 100 healthy/normal participants were used and evaluated. According to ROC analysis, the case prediction performance/accuracy was provided from ANN&LM as %96, AlexNet as %87, ResNet-50 as %95 and CNN&GA as %98.5. The assessment of lung pneumonia in COVID-19 chest CT data was successfully achieved by a product available image processing, ANN and deep learning based approach. With using this, fast and accurate detection and classification stages have … |
| Anahtar Kelimeler |
| Computer aided detection | Computerized Tomography | Interpretation of the abnormality | Lung lesion detection | Novel COVID-19 pneumonia |
BM Sürdürülebilir Kalkınma Amaçları
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| Google Scholar | 3 |