Abstract: Aircraft engines emit particulates that alter the chemical composition of the atmosphere and perturb the Earth’s radiation budget by creating additional ice clouds in the form of condensation trails called contrails. We propose a multi-scale visual computing system that will assist in defining contrail features with parameter analysis for computer-generated aircraft engine simulations. These simulations are computationally intensive and rely on high performance computing (HPC) solutions. Our multi-linked visual system seeks to help in the identification of the formation and evolution of contrails and in the identification of contrail-related spatial features from the simulation workflow.
Approximately 100,000 cases of Head and Neck Cancer (HNC) are diagnosed in the US annually. Patients are increasingly likely to survive, but often experience acute and long term side effects [1]. Hence, great importance has been placed by clinicians on improving patient’s quality of life (QoL) and reducing symptom burden during treatment. We introduce an interactive system which enables clinical and computational experts to visualize and assess medical data. Using novel combinations of visual encodings, our system provides context for new patients based on patients with similar features and symptom evolution, which could help oncologists to create better treatment plans.
@article{floricelvisualizing,title={Visualizing Symptom Development During Head and Neck Cancer Treatment},author={Floricel, Carla and Wentzel, Andrew and Nipu, Md Nafiul and Kumar, Naveen and Canahuate, Guadalupe and Van Dijk, Lisanne and Fuller, C David and Marai, G Elisabeta},booktitle={IEEE Transactions on Visualization and Computer Graphics, Poster Session},year={2020},}
