Pei X - Search Results

1

Gaussian filter facilitated deep learning-based architecture for accurate and efficient liver tumor segmentation for radiation therapy.

Lin H, Zhao M, Zhu L, Pei X, Wu H, Zhang L, Li Y. Lin H, et al. Among authors: pei x. Front Oncol. 2024 Jun 20;14:1423774. doi: 10.3389/fonc.2024.1423774. eCollection 2024. Front Oncol. 2024. PMID: 38966060 Free PMC article.

2

Influencing Factors of Total Skin Irradiation With Helical Tomotherapy.

Wang H, Pi Y, Guo Y, Pei X, Xu XG. Wang H, et al. Among authors: pei x. Front Oncol. 2022 Apr 14;12:852345. doi: 10.3389/fonc.2022.852345. eCollection 2022. Front Oncol. 2022. PMID: 35494075 Free PMC article.

3

A Comparison Study Between CNN-Based Deformed Planning CT and CycleGAN-Based Synthetic CT Methods for Improving iCBCT Image Quality.

Yang B, Chang Y, Liang Y, Wang Z, Pei X, Xu XG, Qiu J. Yang B, et al. Among authors: pei x. Front Oncol. 2022 May 30;12:896795. doi: 10.3389/fonc.2022.896795. eCollection 2022. Front Oncol. 2022. PMID: 35707352 Free PMC article.

4

Adaptive assessment based on fractional CBCT images for cervical cancer.

Chang Y, Liang Y, Wu H, Li L, Yang B, Jiang L, Ren Q, Pei X. Chang Y, et al. Among authors: pei x. J Appl Clin Med Phys. 2024 Oct;25(10):e14462. doi: 10.1002/acm2.14462. Epub 2024 Jul 27. J Appl Clin Med Phys. 2024. PMID: 39072895 Free PMC article.

5

A method of rapid quantification of patient-specific organ doses for CT using deep-learning-based multi-organ segmentation and GPU-accelerated Monte Carlo dose computing.

Peng Z, Fang X, Yan P, Shan H, Liu T, Pei X, Wang G, Liu B, Kalra MK, Xu XG. Peng Z, et al. Among authors: pei x. Med Phys. 2020 Jun;47(6):2526-2536. doi: 10.1002/mp.14131. Epub 2020 Apr 3. Med Phys. 2020. PMID: 32155670

6

A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer.

Zhou J, Peng Z, Song Y, Chang Y, Pei X, Sheng L, Xu XG. Zhou J, et al. Among authors: pei x. J Appl Clin Med Phys. 2020 May;21(5):26-37. doi: 10.1002/acm2.12849. Epub 2020 Apr 13. J Appl Clin Med Phys. 2020. PMID: 32281254 Free PMC article.

7

Evaluation of deep learning-based auto-segmentation algorithms for delineating clinical target volume and organs at risk involving data for 125 cervical cancer patients.

Wang Z, Chang Y, Peng Z, Lv Y, Shi W, Wang F, Pei X, Xu XG. Wang Z, et al. Among authors: pei x. J Appl Clin Med Phys. 2020 Dec;21(12):272-279. doi: 10.1002/acm2.13097. Epub 2020 Nov 25. J Appl Clin Med Phys. 2020. PMID: 33238060 Free PMC article.

8

Clinical Target Volume Auto-Segmentation of Esophageal Cancer for Radiotherapy After Radical Surgery Based on Deep Learning.

Cao R, Pei X, Ge N, Zheng C. Cao R, et al. Among authors: pei x. Technol Cancer Res Treat. 2021 Jan-Dec;20:15330338211034284. doi: 10.1177/15330338211034284. Technol Cancer Res Treat. 2021. PMID: 34387104 Free PMC article.

9

Dosimetric comparison of deformable image registration and synthetic CT generation based on CBCT images for organs at risk in cervical cancer radiotherapy.

Chang Y, Liang Y, Yang B, Qiu J, Pei X, Xu XG. Chang Y, et al. Among authors: pei x. Radiat Oncol. 2023 Jan 5;18(1):3. doi: 10.1186/s13014-022-02191-3. Radiat Oncol. 2023. PMID: 36604687 Free PMC article.

10

A prior-information-based automatic segmentation method for the clinical target volume in adaptive radiotherapy of cervical cancer.

Wang X, Chang Y, Pei X, Xu XG. Wang X, et al. Among authors: pei x. J Appl Clin Med Phys. 2024 May;25(5):e14350. doi: 10.1002/acm2.14350. Epub 2024 Mar 28. J Appl Clin Med Phys. 2024. PMID: 38546277 Free PMC article.

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