Mutlu Demirer
Orcid: 0000-0002-6842-282X
According to our database1,
Mutlu Demirer
authored at least 13 papers
between 2018 and 2023.
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Bibliography
2023
Integration and Implementation Strategies for AI Algorithm Deployment with Smart Routing Rules and Workflow Management.
CoRR, 2023
Breast-Density Semantic Segmentation with Probability Scaling for BI-RADS Assessment using DeepLabV3.
Proceedings of the 14th ACM International Conference on Bioinformatics, 2023
2022
CoRR, 2022
Impact of Concatenation of Digital Craniocaudal Mammography Images on a Deep-Learning Breast-Density Classifier Using Inception-V3 and ViT.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022
2021
Artificial Intelligence to Assist in Exclusion of Coronary Atherosclerosis During CCTA Evaluation of Chest Pain in the Emergency Department: Preparing an Application for Real-world Use.
J. Digit. Imaging, 2021
Cascading Neural Network Methodology for Artificial Intelligence-Assisted Radiographic Detection and Classification of Lead-Less Implanted Electronic Devices within the Chest.
CoRR, 2021
2020
Automated Brain Metastases Detection Framework for T1-Weighted Contrast-Enhanced 3D MRI.
IEEE J. Biomed. Health Informatics, 2020
Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning.
J. Digit. Imaging, 2020
Automated coronary artery atherosclerosis detection and weakly supervised localization on coronary CT angiography with a deep 3-dimensional convolutional neural network.
Comput. Medical Imaging Graph., 2020
Using Transfer Learning and Class Activation Maps Supporting Detection and Localization of Femoral Fractures on Anteroposterior Radiographs.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
2019
Coronary Artery Classification and Weakly Supervised Abnormality Localization on Coronary CT Angiography with 3-Dimensional Convolutional Neural Networks.
CoRR, 2019
Are Quantitative Features of Lung Nodules Reproducible at Different CT Acquisition and Reconstruction Parameters?
CoRR, 2019
2018