Mason J Belue
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Explore the profile of Mason J Belue including associated specialties, affiliations and a list of published articles.
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80
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Recent Articles
1.
Esengur O, Yilmaz E, Simon B, Harmon S, Gelikman D, Lin Y, et al.
Acad Radiol
. 2025 Jan;
PMID: 39809601
Rationale And Objectives: Accurate preoperative mpMRI-based detection of extraprostatic extension (EPE) in prostate cancer (PCa) is critical for surgical planning and patient outcomes. This study aims to evaluate the impact...
2.
Yilmaz E, Harmon S, Law Y, Huang E, Belue M, Lin Y, et al.
Radiol Imaging Cancer
. 2024 Oct;
6(6):e240050.
PMID: 39400232
Purpose To evaluate the performance of an artificial intelligence (AI) model in detecting overall and clinically significant prostate cancer (csPCa)-positive lesions on paired external and in-house biparametric MRI (bpMRI) scans...
3.
Belue M, Harmon S, Chappidi S, Zhuge Y, Tasci E, Jagasia S, et al.
Diagnostics (Basel)
. 2024 Jul;
14(13).
PMID: 39001264
Glioblastoma (GBM) is the most aggressive and the most common primary brain tumor, defined by nearly uniform rapid progression despite the current standard of care involving maximal surgical resection followed...
4.
Lin Y, Belue M, Yilmaz E, Law Y, Merriman K, Phelps T, et al.
Abdom Radiol (NY)
. 2024 Jul;
49(8):2891-2901.
PMID: 38958754
Objective: To assess impact of image quality on prostate cancer extraprostatic extension (EPE) detection on MRI using a deep learning-based AI algorithm. Materials And Methods: This retrospective, single institution study...
5.
Lin Y, Yilmaz E, Belue M, Harmon S, Tetreault J, Phelps T, et al.
Radiology
. 2024 May;
311(2):e230750.
PMID: 38713024
Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models...
6.
Johnson L, Harmon S, Yilmaz E, Lin Y, Belue M, Merriman K, et al.
Abdom Radiol (NY)
. 2024 Mar;
49(5):1545-1556.
PMID: 38512516
Objective: Automated methods for prostate segmentation on MRI are typically developed under ideal scanning and anatomical conditions. This study evaluates three different prostate segmentation AI algorithms in a challenging population...
7.
Belue M, Harmon S, Yang D, An J, Gaur S, Law Y, et al.
Acad Radiol
. 2024 Jan;
31(6):2424-2433.
PMID: 38262813
Rationale And Objectives: Efficiently detecting and characterizing metastatic bone lesions on staging CT is crucial for prostate cancer (PCa) care. However, it demands significant expert time and additional imaging such...
8.
Belue M, Harmon S, Masoudi S, Barrett T, Law Y, Purysko A, et al.
Eur J Radiol
. 2023 Dec;
170:111259.
PMID: 38128256
Purpose: To evaluate CycleGAN's ability to enhance T2-weighted image (T2WI) quality. Method: A CycleGAN algorithm was used to enhance T2WI quality. 96 patients (192 scans) were identified from patients who...
9.
Belue M, Law Y, Marko J, Turkbey E, Malayeri A, Yilmaz E, et al.
Acad Radiol
. 2023 Oct;
31(4):1429-1437.
PMID: 37858505
Rationale And Objectives: Prostate MRI quality is essential in guiding prostate biopsies. However, assessment of MRI quality is subjective with variation. Quality degradation sources exert varying impacts based on the...
10.
Lin Y, Belue M, Yilmaz E, Harmon S, An J, Law Y, et al.
J Magn Reson Imaging
. 2023 Oct;
59(6):2215-2223.
PMID: 37811666
Background: Image quality evaluation of prostate MRI is important for successful implementation of MRI into localized prostate cancer diagnosis. Purpose: To examine the impact of image quality on prostate cancer...