44 citations · 87 across the 11 of their papers we have counts for
11 papers
A Radiomics-Incorporated Deep Ensemble Learning Model for Multi-Parametric MRI-based Glioma Segmentation
Yang Chen, Zhenyu Yang, Jingtong Zhao +4
We developed a deep ensemble learning model with a radiomics spatial encoding execution for improved glioma segmentation accuracy using multi-parametric MRI (mp-MRI). This model wa…
Quantifying U-Net Uncertainty in Multi-Parametric MRI-based Glioma Segmentation by Spherical Image Projection
Zhenyu Yang, Kyle Lafata, Eugene Vaios +4
The projection of planar MRI data onto a spherical surface is equivalent to a nonlinear image transformation that retains global anatomical information. By incorporating this image…
A Neural Ordinary Differential Equation Model for Visualizing Deep Neural Network Behaviors in Multi-Parametric MRI based Glioma Segmentation
Zhenyu Yang, Zongsheng Hu, Hangjie Ji +4
Purpose: To develop a neural ordinary differential equation (ODE) model for visualizing deep neural network (DNN) behavior during multi-parametric MRI (mp-MRI) based glioma segment…
A Deep Learning Model with Radiomics Analysis Integration for Glioblastoma Post-Resection Survival Prediction
Zongsheng Hu, Zhenyu Yang, Haozhao Zhang +4
Purpose: To develop a novel deep-learning model that integrates radiomics analysis in a multi-dimensional feature fusion workflow for glioblastoma (GBM) post-resection survival pre…
A Radiomics-Boosted Deep-Learning Model for COVID-19 and Non-COVID-19 Pneumonia Classification Using Chest X-ray Image
Zongsheng Hu, Zhenyu Yang, Kyle J. Lafata +2
To develop a deep-learning model that integrates radiomics analysis for enhanced performance of COVID-19 and Non-COVID-19 pneumonia detection using chest X-ray image, two deep-lear…
Post-Radiotherapy PET Image Outcome Prediction by Deep Learning under Biological Model Guidance: A Feasibility Study of Oropharyngeal Cancer Application
Hangjie Ji, Kyle Lafata, Yvonne Mowery +4
This paper develops a method of biologically guided deep learning for post-radiation FDG-PET image outcome prediction based on pre-radiation images and radiotherapy dose informatio…
Quantification of lung function on CT images based on pulmonary radiomic filtering
Zhenyu Yang, Kyle J Lafata, Xinru Chen +4
Purpose: To develop a radiomics filtering technique for characterizing spatial-encoded regional pulmonary ventilation information on lung CT. Methods: The lung volume was segmented…
An interpretable planning bot for pancreas stereotactic body radiation therapy
Jiahan Zhang, Chunhao Wang, Yang Sheng +9
Pancreas stereotactic body radiotherapy treatment planning requires planners to make sequential, time consuming interactions with the treatment planning system (TPS) to reach the o…
An Artificial Intelligence-Driven Agent for Real-Time Head-and-Neck IMRT Plan Generation using Conditional Generative Adversarial Network (cGAN)
Xinyi Li, Yang Sheng, Jiahan Zhang +6
Purpose: To develop an Artificial Intelligence (AI) agent for fully-automated rapid head and neck (H&N) IMRT plan generation without time-consuming inverse planning.$$$$ Methods: T…
Data clustering based on Langevin annealing with a self-consistent potential
Kyle Lafata, Zhennan Zhou, Jian-Guo Liu +1
This paper introduces a novel data clustering algorithm based on Langevin dynamics, where the associated potential is constructed directly from the data. To introduce a self-consis…
Iterative Inversion of Deformation Vector Fields with Feedback Control
Abhishek Kumar Dubey, Alexandros-Stavros Iliopoulos, Xiaobai Sun +2
Purpose: Often, the inverse deformation vector field (DVF) is needed together with the corresponding forward DVF in 4D reconstruction and dose calculation, adaptive radiation thera…