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Barbara Marquez

Explore the profile of Barbara Marquez including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 8
Citations 43
Followers 0
Related Specialties
Oncology
Radiology
Biophysics
Top 10 Co-Authors
Laurence E Court
Tucker J Netherton
Carlos E Cardenas
Clifton D Fuller
Mary P Gronberg
David Fuentes
Christine B Peterson
Kareem A Wahid
Skylar Gay
Anuja Jhingran
Published In
Diagnostics (Basel)
Pract Radiat Oncol
Front Oncol
Use Comput Radiat Ther
ArXiv
Affiliations
Soon will be listed here.
Recent Articles
1.
OAR-Weighted Dice Score: A spatially aware, radiosensitivity aware metric for target structure contour quality assessment
McCullum L, Wahid K, Marquez B, Fuller C
Use Comput Radiat Ther . 2024 Nov; 2024:755-758. PMID: 39512542
The Dice Similarity Coefficient (DSC) is the current standard to determine agreement between a reference segmentation and one generated by manual / auto-contouring approaches. This metric is useful for non-spatially...
2.
Analyzing the Relationship between Dose and Geometric Agreement Metrics for Auto-Contouring in Head and Neck Normal Tissues
Marquez B, Wooten Z, Salazar R, Peterson C, Fuentes D, Whitaker T, et al.
Diagnostics (Basel) . 2024 Aug; 14(15). PMID: 39125508
This study aimed to determine the relationship between geometric and dosimetric agreement metrics in head and neck (H&N) cancer radiotherapy plans. A total 287 plans were retrospectively analyzed, comparing auto-contoured...
3.
Evolving Horizons in Radiation Therapy Auto-Contouring: Distilling Insights, Embracing Data-Centric Frameworks, and Moving Beyond Geometric Quantification
Wahid K, Cardenas C, Marquez B, Netherton T, Kann B, Court L, et al.
Adv Radiat Oncol . 2024 May; 9(7):101521. PMID: 38799110
No abstract available.
4.
Evolving Horizons in Radiotherapy Auto-Contouring: Distilling Insights, Embracing Data-Centric Frameworks, and Moving Beyond Geometric Quantification
Wahid K, Cardenas C, Marquez B, Netherton T, Kann B, Court L, et al.
ArXiv . 2023 Oct; PMID: 37904737
No abstract available.
5.
A real-time contouring feedback tool for consensus-based contour training
Nelson C, Nguyen C, Fang R, Court L, Cardenas C, Rhee D, et al.
Front Oncol . 2023 Sep; 13:1204323. PMID: 37771435
Purpose: Variability in contouring structures of interest for radiotherapy continues to be challenging. Although training can reduce such variability, having radiation oncologists provide feedback can be impractical. We developed a...
6.
Deep learning-based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers
Gronberg M, Jhingran A, Netherton T, Gay S, Cardenas C, Chung C, et al.
Med Phys . 2023 Sep; 50(11):6639-6648. PMID: 37706560
Background: In recent years, deep-learning models have been used to predict entire three-dimensional dose distributions. However, the usability of dose predictions to improve plan quality should be further investigated. Purpose:...
7.
Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?
Baroudi H, Brock K, Cao W, Chen X, Chung C, Court L, et al.
Diagnostics (Basel) . 2023 Feb; 13(4). PMID: 36832155
Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is 'clinical acceptability'? Quantitative and...
8.
Deep Learning-Based Dose Prediction for Automated, Individualized Quality Assurance of Head and Neck Radiation Therapy Plans
Gronberg M, Beadle B, Garden A, Skinner H, Gay S, Netherton T, et al.
Pract Radiat Oncol . 2023 Jan; 13(3):e282-e291. PMID: 36697347
Purpose: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans. Methods And Materials: A total of 245 volumetric...