Gengyan Zhao
Overview
Explore the profile of Gengyan Zhao including associated specialties, affiliations and a list of published articles.
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Articles
12
Citations
349
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Recent Articles
1.
Yoo Y, Gibson E, Zhao G, Re T, Parmar H, Das J, et al.
Int J Radiat Oncol Biol Phys
. 2024 Jul;
121(1):241-249.
PMID: 39059508
Purpose: The purpose of this study was to investigate an extended self-adapting nnU-Net framework for detecting and segmenting brain metastases (BM) on magnetic resonance imaging (MRI). Methods And Materials: Six...
2.
Kim J, Oh S, Lee H, Choi M, Meyer H, Huwer S, et al.
Acad Radiol
. 2024 Jun;
31(11):4621-4628.
PMID: 38908922
Rationale And Objectives: To assess a deep learning application (DLA) for acute ischemic stroke (AIS) detection on brain magnetic resonance imaging (MRI) in the emergency room (ER) and the effect...
3.
Das B, Zhao G, Islam S, Re T, Comaniciu D, Gibson E, et al.
Sci Rep
. 2024 Apr;
14(1):9380.
PMID: 38654066
Vision transformers (ViTs) have revolutionized computer vision by employing self-attention instead of convolutional neural networks and demonstrated success due to their ability to capture global dependencies and remove spatial biases...
4.
Liu Y, Nacewicz B, Zhao G, Adluru N, Kirk G, Ferrazzano P, et al.
Front Neurosci
. 2020 Jun;
14:260.
PMID: 32508558
Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorders. However, most existing deep learning...
5.
Hwang G, Hermann B, Nair V, Conant L, Dabbs K, Mathis J, et al.
Neuroimage Clin
. 2020 Feb;
25:102183.
PMID: 32058319
The association of epilepsy with structural brain changes and cognitive abnormalities in midlife has raised concern regarding the possibility of future accelerated brain and cognitive aging and increased risk of...
6.
Hwang G, Nair V, Mathis J, Cook C, Mohanty R, Zhao G, et al.
Brain Connect
. 2019 Feb;
9(2):184-193.
PMID: 30803273
The National Institutes of Health-sponsored Epilepsy Connectome Project aims to characterize connectivity changes in temporal lobe epilepsy (TLE) patients. The magnetic resonance imaging protocol follows that used in the Human...
7.
Liu F, Jang H, Kijowski R, Zhao G, Bradshaw T, McMillan A
EJNMMI Phys
. 2018 Nov;
5(1):24.
PMID: 30417316
Background: To develop and evaluate the feasibility of a data-driven deep learning approach (deepAC) for positron-emission tomography (PET) image attenuation correction without anatomical imaging. A PET attenuation correction pipeline was...
8.
Bradshaw T, Zhao G, Jang H, Liu F, McMillan A
Tomography
. 2018 Oct;
4(3):138-147.
PMID: 30320213
This study evaluated the feasibility of using only diagnostically relevant magnetic resonance (MR) images together with deep learning for positron emission tomography (PET)/MR attenuation correction (deepMRAC) in the pelvis. Such...
9.
Zhou Z, Zhao G, Kijowski R, Liu F
Magn Reson Med
. 2018 May;
80(6):2759-2770.
PMID: 29774599
Purpose: To describe and evaluate a new segmentation method using deep convolutional neural network (CNN), 3D fully connected conditional random field (CRF), and 3D simplex deformable modeling to improve the...
10.
Jang H, Liu F, Zhao G, Bradshaw T, McMillan A
Med Phys
. 2018 May;
PMID: 29763997
Purpose: In this study, we explore the feasibility of a novel framework for MR-based attenuation correction for PET/MR imaging based on deep learning via convolutional neural networks, which enables fully...