Early Detection of Lymph Node Metastasis Using Primary Head and Neck Cancer Computed Tomography and Fluorescence Lifetime Imaging.

Autor: Yuan, Nimu¹ (AUTHOR) nmyuan@ucdavis.edu, Hassan, Mohamed A.¹ (AUTHOR) mahmohamed@ucdavis.edu, Ehrlich, Katjana¹ (AUTHOR) kehr@ucdavis.edu, Weyers, Brent W.¹ (AUTHOR) brentwweyers@gmail.com, Biddle, Garrick² (AUTHOR) gbiddle@ucdavis.edu, Ivanovic, Vladimir³ (AUTHOR) vivanovic@ucdavis.edu, Raslan, Osama A. A.² (AUTHOR) oraslan@ucdavis.edu, Gui, Dorina⁴ (AUTHOR) dgui@ucdavis.edu, Abouyared, Marianne⁵ (AUTHOR) mabouyared@ucdavis.edu, Bewley, Arnaud F.⁵ (AUTHOR) abewley@ucdavis.edu, Birkeland, Andrew C.⁵ (AUTHOR) acbirkeland@ucdavis.edu, Farwell, D. Gregory⁶ (AUTHOR) greg.farwell@pennmedicine.upenn.edu, Marcu, Laura^1,7 (AUTHOR) lmarcu@ucdavis.edu, Qi, Jinyi¹ (AUTHOR) lmarcu@ucdavis.edu

Publikováno v: Diagnostics (2075-4418). Sep2024, Vol. 14 Issue 18, p2097. 14p.

Clinical Enhancement in AI-Based Post-processed Fast-Scan Low-Dose CBCT for Head and Neck Adaptive Radiotherapy

Autor: Chen, Wen, Li, Yimin, Yuan, Nimu, Qi, Jinyi, Dyer, Brandon A, Sensoy, Levent, Benedict, Stanley H, Shang, Lu, Rao, Shyam, Rong, Yi

Purpose: To assess image quality and uncertainty in organ-at-risk segmentation on cone beam computed tomography (CBCT) enhanced by deep-learning convolutional neural network (DCNN) for head and neck cancer. Methods: An in-house DCNN was trained using

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::0a4bf2ee4bf1accc260800abd446e343
https://escholarship.org/uc/item/0jk710r5

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Low-dose CT image denoising without high-dose reference images

Autor: Matej, Samuel, Metzler, Scott D., Yuan, Nimu, Zhou, Jian, Qi, Jinyi

Publikováno v: Proceedings of SPIE; May 2019, Vol. 11072 Issue: 1 p110721C-110721C-5, 996495p

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