10 citations · 13 across the 4 of their papers we have counts for
4 papers
Deep Learning Based Apparent Diffusion Coefficient Map Generation from Multi-parametric MR Images for Patients with Diffuse Gliomas
Zach Eidex, Mojtaba Safari, Jacob Wynne +6
Purpose: Apparent diffusion coefficient (ADC) maps derived from diffusion weighted (DWI) MRI provides functional measurements about the water molecules in tissues. However, DWI is…
Artificial Intelligence-based Motion Tracking in Cancer Radiotherapy: A Review
Elahheh Salari, Jing Wang, Jacob Wynne +2
Radiotherapy aims to deliver a prescribed dose to the tumor while sparing neighboring organs at risk (OARs). Increasingly complex treatment techniques such as volumetric modulated…
Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Model
Shaoyan Pan, Elham Abouei, Jacob Wynne +10
Magnetic resonance imaging (MRI)-based synthetic computed tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for CT simulation and error-prone…
Deep Learning-based Multi-Organ CT Segmentation with Adversarial Data Augmentation
Shaoyan Pan, Shao-Yuan Lo, Min Huang +5
In this work, we propose an adversarial attack-based data augmentation method to improve the deep-learning-based segmentation algorithm for the delineation of Organs-At-Risk (OAR)…