333 citations · 372 across the 6 of their papers we have counts for
6 papers
HydraViT: Adaptive Multi-Branch Transformer for Multi-Label Disease Classification from Chest X-ray Images
Şaban Öztürk, M. Yiğit Turalı, Tolga Çukur
Chest X-ray is an essential diagnostic tool in the identification of chest diseases given its high sensitivity to pathological abnormalities in the lungs. However, image-driven dia…
Content-Based Medical Image Retrieval with Opponent Class Adaptive Margin Loss
Şaban Öztürk, Emin Celik, Tolga Cukur
Broadspread use of medical imaging devices with digital storage has paved the way for curation of substantial data repositories. Fast access to image samples with similar appearanc…
Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
Saban Ozturk, Tolga Cukur
Melanoma is a fatal skin cancer that is curable and has dramatically increasing survival rate when diagnosed at early stages. Learning-based methods hold significant promise for th…
Classification of COVID-19 in Chest CT Images using Convolutional Support Vector Machines
Umut Özkaya, Şaban Öztürk, Serkan Budak +2
Purpose: Coronavirus 2019 (COVID-19), which emerged in Wuhan, China and affected the whole world, has cost the lives of thousands of people. Manual diagnosis is inefficient due to…
Coronavirus (COVID-19) Classification using Deep Features Fusion and Ranking Technique
Umut Ozkaya, Saban Ozturk, Mucahid Barstugan
Coronavirus (COVID-19) emerged towards the end of 2019. World Health Organization (WHO) was identified it as a global epidemic. Consensus occurred in the opinion that using Compute…
Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods
Mucahid Barstugan, Umut Ozkaya, Saban Ozturk
This study presents early phase detection of Coronavirus (COVID-19), which is named by World Health Organization (WHO), by machine learning methods. The detection process was imple…