4 citations · 9 across the 5 of their papers we have counts for
5 papers
Uncertainty-Guided Coarse-to-Fine Tumor Segmentation with Anatomy-Aware Post-Processing
Ilkin Sevgi Isler, David Mohaisen, Curtis Lisle +2
Reliable tumor segmentation in thoracic computed tomography (CT) remains challenging due to boundary ambiguity, class imbalance, and anatomical variability. We propose an uncertain…
Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning
Zheyuan Zhang, Elif Keles, Gorkem Durak +35
Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis and follow-up of pancreatic diseases. While CT-based pancreatic segmentation is…
Self-Supervised Learning for Organs At Risk and Tumor Segmentation with Uncertainty Quantification
Ilkin Isler, Debesh Jha, Curtis Lisle +6
In this study, our goal is to show the impact of self-supervised pre-training of transformers for organ at risk (OAR) and tumor segmentation as compared to costly fully-supervised…
Enhancing Organ at Risk Segmentation with Improved Deep Neural Networks
Ilkin Isler, Curtis Lisle, Justin Rineer +4
Organ at risk (OAR) segmentation is a crucial step for treatment planning and outcome determination in radiotherapy treatments of cancer patients. Several deep learning based segme…
Facial Expression Recognition Using Human to Animated-Character Expression Translation
Kamran Ali, Ilkin Isler, Charles Hughes
Facial expression recognition is a challenging task due to two major problems: the presence of inter-subject variations in facial expression recognition dataset and impure expressi…