Sex estimation with convolutional neural networks using the patella magnetic resonance image slices
Published in Computational Sciences
In this study, sex estimation was performed with the EfficientNetB3, MobileNetV2, Visual Geometry Group 16 (VGG16), ResNet50, and DenseNet121 architectures on patellar magnetic resonance images via a developed model. Within the scope of the study, 6710 magnetic resonance sagittal patella image The performance of artificial intelligence algorithms was examined through deep learning architectures and the developed classification model. Considering the performance evaluation criteria, the best accuracy result of 88.88% was obtained with the ResNet50 model. In addition, the proposed model was among the best-performing models with an accuracy of 85.70%. When all these results were examined, it was concluded that positive sex estimation results could be obtained from patella magnetic resonance image (MRI) slices without the use of the morphometric method.
Dr. Gökalp Çınarer is an Assistant Professor in the Department of Computer Engineering at Yozgat Bozok University. He completed his PhD in Computer Engineering at Kırıkkale University between 2017-2021 and wrote his thesis on "Detection of Brain Tumors with Image Processing Techniques and Analysis with Classification Algorithms".
His research interests focus on artificial intelligence, machine learning, image processing and deep neural networks. He has carried out important academic studies using artificial intelligence applications in different fields such as medicine, agriculture, food technologies and environmental analysis.
Since 2021, he has been continuing his administrative duties as the Head of the Department of Information Processing and Head of the Department of Computer Engineering Software at Yozgat Bozok University. He teaches undergraduate and graduate courses such as Machine Learning, Deep Learning, Python Programming, Algorithm Analysis, Artificial Intelligence Applications.
His academic publications include more than 75 articles scanned by SCI-Expanded, SSCI and Scopus, and international conference proceedings. His work covers various topics such as brain tumor analysis with artificial intelligence, artificial intelligence applications in agriculture, environmental data analysis and object detection.
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https://docs.google.com/document/d/12584o9sol-RpSsbLonLkIewdVtiwvqX7gHy_k8CHTg8/edit?usp=sharing