Riqiang Gao
Overview
Explore the profile of Riqiang Gao including associated specialties, affiliations and a list of published articles.
Author names and details appear as published. Due to indexing inconsistencies, multiple individuals may share a name, and a single author may have variations. MedLuna displays this data as publicly available, without modification or verification
Snapshot
Snapshot
Articles
37
Citations
162
Followers
0
Related Specialties
Related Specialties
Top 10 Co-Authors
Top 10 Co-Authors
Published In
Published In
Affiliations
Affiliations
Soon will be listed here.
Recent Articles
1.
Arberet S, Ghesu F, Gao R, Kraus M, Sackett J, Kuusela E, et al.
Med Phys
. 2025 Feb;
PMID: 39935217
Background: Volumetric modulated arc therapy (VMAT) revolutionizes cancer treatment by precisely delivering radiation while sparing healthy tissues. Fluence maps generation, crucial in VMAT planning, traditionally involves complex and iterative, and...
2.
Li T, Xu K, Krishnan A, Gao R, Kammer M, Antic S, et al.
Radiol Artif Intell
. 2025 Feb;
7(2):e230506.
PMID: 39907586
Purpose To evaluate the performance of eight lung cancer prediction models on patient cohorts with screening-detected, incidentally detected, and bronchoscopically biopsied pulmonary nodules. Materials and Methods This study retrospectively evaluated...
3.
Li T, Still J, Xu K, Lee H, Cai L, Krishnan A, et al.
Med Image Comput Comput Assist Interv
. 2024 May;
14221:649-659.
PMID: 38779102
The accuracy of predictive models for solitary pulmonary nodule (SPN) diagnosis can be greatly increased by incorporating repeat imaging and medical context, such as electronic health records (EHRs). However, clinically...
4.
Yu X, Yang Q, Tang Y, Gao R, Bao S, Cai L, et al.
J Med Imaging (Bellingham)
. 2024 Apr;
11(2):024008.
PMID: 38571764
Purpose: Two-dimensional single-slice abdominal computed tomography (CT) provides a detailed tissue map with high resolution allowing quantitative characterization of relationships between health conditions and aging. However, longitudinal analysis of body...
5.
Liu H, Xu Z, Gao R, Li H, Wang J, Chabin G, et al.
IEEE Trans Med Imaging
. 2024 Jan;
43(5):1995-2009.
PMID: 38224508
Deep learning models have demonstrated remarkable success in multi-organ segmentation but typically require large-scale datasets with all organs of interest annotated. However, medical image datasets are often low in sample...
6.
Yu X, Yang Q, Zhou Y, Cai L, Gao R, Lee H, et al.
Med Image Anal
. 2023 Sep;
90:102939.
PMID: 37725868
Transformer-based models, capable of learning better global dependencies, have recently demonstrated exceptional representation learning capabilities in computer vision and medical image analysis. Transformer reformats the image into separate patches and...
7.
Xu K, Khan M, Li T, Gao R, Terry J, Huo Y, et al.
Radiology
. 2023 Jul;
308(1):e222937.
PMID: 37489991
Background An artificial intelligence (AI) algorithm has been developed for fully automated body composition assessment of lung cancer screening noncontrast low-dose CT of the chest (LDCT) scans, but the utility...
8.
Li T, Lee H, Xu K, Gao R, Dawant B, Maldonado F, et al.
J Med Imaging (Bellingham)
. 2023 Jul;
10(4):044002.
PMID: 37469854
Purpose: Anatomy-based quantification of emphysema in a lung screening cohort has the potential to improve lung cancer risk stratification and risk communication. Segmenting lung lobes is an essential step in...
9.
Xu K, Khan M, Li T, Gao R, Antic S, Huo Y, et al.
Proc SPIE Int Soc Opt Eng
. 2023 Jul;
12464.
PMID: 37465098
In lung cancer screening, estimation of future lung cancer risk is usually guided by demographics and smoking status. The role of constitutional profiles of human body, a.k.a. body habitus, is...
10.
Li T, Xu K, Gao R, Tang Y, Lasko T, Maldonado F, et al.
Proc SPIE Int Soc Opt Eng
. 2023 Jul;
12464.
PMID: 37465096
Features learned from single radiologic images are unable to provide information about whether and how much a lesion may be changing over time. Time-dependent features computed from repeated images can...