6 citations · 14 across the 7 of their papers we have counts for
6 papers · 1 filter
High-resolution 3T to 7T MRI Synthesis with a Hybrid CNN-Transformer Model
Zach Eidex, Jing Wang, Mojtaba Safari +6
7 Tesla (7T) apparent diffusion coefficient (ADC) maps derived from diffusion-weighted imaging (DWI) demonstrate improved image quality and spatial resolution over 3 Tesla (3T) ADC…
Hippocampus Substructure Segmentation Using Morphological Vision Transformer Learning
Yang Lei, Yifu Ding, Richard L. J. Qiu +6
Background: The hippocampus plays a crucial role in memory and cognition. Because of the associated toxicity from whole brain radiotherapy, more advanced treatment planning techniq…
Denoising Magnetic Resonance Spectroscopy (MRS) Data Using Stacked Autoencoder for Improving Signal-to-Noise Ratio and Speed of MRS
Jing Wang, Bing Ji, Yang Lei +3
Background: Magnetic resonance spectroscopy (MRS) enables non-invasive detection and measurement of biochemicals and metabolites. However, MRS has low signal-to-noise ratio (SNR) w…
Radiomics in Cancer Radiotherapy: a Review
Jiwoong Jeong, Arif Ali, Tian Liu +3
Radiomics is a nascent field in quantitative imaging that uses advanced algorithms and considerable computing power to describe tumor phenotypes, monitor treatment response, and as…
Machine-learning-based Classification of Lower-grade gliomas and High-grade gliomas using Radiomic Features in Multi-parametric MRI
Ge Cui, Jiwoong Jeong, Bob Press +6
Objectives: Glioblastomas are the most aggressive brain and central nervous system (CNS) tumors with poor prognosis in adults. The purpose of this study is to develop a machine-lea…
Air, bone and soft-tissue Segmentation on 3D brain MRI Using Semantic Classification Random Forest with Auto-Context Model
Xue Dong, Yang Lei, Sibo Tian +7
As bone and air produce weak signals with conventional MR sequences, segmentation of these tissues particularly difficult in MRI. We propose to integrate patch-based anatomical sig…