Ulaş Bağcı

Research interests

Publications

• Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation

  · 2024 · 10.1109/wacv57701.2024.00132

• Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions

  IEEE Internet of Things Journal · 2023 · https://doi.org/10.1109/jiot.2023.3329061

• Real-time Multi-Class Helmet Violation Detection Using Few-Shot Data Sampling Technique and YOLOv8

  · 2023 · 10.1109/cvprw59228.2023.00564

• TGANet: Text-Guided Attention for Improved Polyp Segmentation

  Lecture notes in computer science · 2022 · 10.1007/978-3-031-16437-8_15

• EEG Based Classification of Long-Term Stress Using Psychological Labeling

  Sensors · 2020 · 10.3390/s20071886

• Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets

  Nature Communications · 2020 · https://doi.org/10.1038/s41467-020-17971-2

• RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge

  IEEE Transactions on Medical Imaging · 2019 · 10.1109/tmi.2019.2901398

• Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches

  IEEE Transactions on Medical Imaging · 2019 · 10.1109/tmi.2019.2894349

• Quality assurance of computer-aided detection and diagnosis in colonoscopy

  Gastrointestinal Endoscopy · 2019 · 10.1016/j.gie.2019.03.019

• Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge

  Medical Image Analysis · 2019 · https://doi.org/10.1016/j.media.2019.101537

• Capsules for Object Segmentation

  arXiv (Cornell University) · 2018 · 10.48550/arxiv.1804.04241

• Deep learning beyond cats and dogs: recent advances in diagnosing breast cancer with deep neural networks

  British Journal of Radiology · 2018 · 10.1259/bjr.20170545

• Deep Geodesic Learning for Segmentation and Anatomical Landmarking

  IEEE Transactions on Medical Imaging · 2018 · 10.1109/tmi.2018.2875814

• How to fool radiologists with generative adversarial networks? A visual turing test for lung cancer diagnosis

  · 2018 · 10.1109/isbi.2018.8363564

• How to fool radiologists with generative adversarial networks? A visual turing test for lung cancer diagnosis

  · 2018 · 10.1109/isbi.2018.8363564

• Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning

  Lecture notes in computer science · 2017 · 10.1007/978-3-319-59050-9_20

• Holistic classification of CT attenuation patterns for interstitial lung diseases via deep convolutional neural networks

  Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization · 2016 · 10.1080/21681163.2015.1124249

• Evaluation of candidate vaccine approaches for MERS-CoV

  Nature Communications · 2015 · https://doi.org/10.1038/ncomms8712

• Segmentation and Image Analysis of Abnormal Lungs at CT: Current Approaches, Challenges, and Future Trends

  Radiographics · 2015 · 10.1148/rg.2015140232

• A Generic Approach to Pathological Lung Segmentation

  IEEE Transactions on Medical Imaging · 2014 · 10.1109/tmi.2014.2337057

• A review on segmentation of positron emission tomography images

  Computers in Biology and Medicine · 2014 · https://doi.org/10.1016/j.compbiomed.2014.04.014

• Joint segmentation of anatomical and functional images: Applications in quantification of lesions from PET, PET-CT, MRI-PET, and MRI-PET-CT images

  Medical Image Analysis · 2013 · 10.1016/j.media.2013.05.004

• Medical Image Segmentation by Combining Graph Cuts and Oriented Active Appearance Models

  IEEE Transactions on Image Processing · 2012 · 10.1109/tip.2012.2186306

Current projects

No projects listed.