Search Results - "Lin, Mu-Han"

Clinical Implementation of PSMA-PET Guided Tumor Response-Based Boost Adaptation in Online Adaptive Radiotherapy for High-Risk Prostate Cancer.

Authors: Li, Ruiqi Lin, Mu-Han Nguyen, Nghi C. et al.

Source: Cancers. Sep2025, Vol. 17 Issue 17, p2893. 12p.

Best Practice: CT‐guided Adaptive Radiotherapy Reference Planning on the Ethos Platform.

Authors: Ray, Xenia Harms, Joseph Price, Alex et al.

Source: Journal of Applied Clinical Medical Physics; May2026, Vol. 27 Issue 5, p1-15, 15p

Strategies for enhancing delivery efficiency on MR‐Linac: A dosimetric study and historical plan review.

Authors: Zhang, Ying Tang, Shanshan Kabat, Christopher et al.

Source: Journal of Applied Clinical Medical Physics; May2026, Vol. 27 Issue 5, p1-12, 12p

Adapt‐on‐demand: Enabling flexible and scalable adaptive radiotherapy through workflow automation.

Authors: Domal, Sean Choi, Min Geon Visak, Justin et al.

Source: Journal of Applied Clinical Medical Physics; May2026, Vol. 27 Issue 5, p1-9, 9p

Development and implementation of an MRI‐only simulation, planning, and treatment workflow for prostate radiotherapy using synthetic CT on MR‐linac.

Authors: Reiazi, Reza Ding, Yao Vijayan, Sarath et al.

Source: Journal of Applied Clinical Medical Physics; Feb2026, Vol. 27 Issue 2, p1-11, 11p

Afatinib Versus Osimertinib as First-Line Treatment for Advanced EGFR-Mutant Non-Small-Cell Lung Cancer: A 3-Year Follow-Up Overall Survival Analysis.

Authors: Huang YH Hsu KH Tseng JS et al.

Source: Targeted oncology [Target Oncol] 2026 Jun 08. Date of Electronic Publication: 2026 Jun 08.

Publication Type: Journal Article

Journal Info: Publisher: Springer-Verlag France Country of Publication: France NLM ID: 101270595 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1776-260X (Electronic) Linking ISSN: 17762596 NLM ISO Abbreviation: Target Oncol Subsets: MEDLINE

Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy (PULSAR) for Patients with Lung Tumors and Severe Pulmonary Disease.

Authors: Westover, Kenneth D. Li, Ruiqi Tanner, Stetler et al.

Source: Journal of Clinical Medicine. Feb2026, Vol. 15 Issue 3, p1261. 12p.

Artificial Intelligence in Image Assisted Radiation Oncology.

Authors: Wang, He Zhao, Yao Chen, Xinru et al.

Source: Cancers. Jun2026, Vol. 18 Issue 11, p1715. 47p.

Development and clinical implementation of an MRI‐only planning workflow featuring deep learning‐based synthetic CT for prostate cancer external beam radiotherapy.

Authors: Deng, Jie Liang, Xiao Iakovenko, Viktor et al.

Source: Journal of Applied Clinical Medical Physics; Sep2025, Vol. 26 Issue 9, p1-14, 14p

Improving efficiency in lung SAbR planning using integrated tools for X‐ray based adaptive radiotherapy.

Authors: Visak, Justin Washington, Brien Liao, Chien‐Yi et al.

Source: Journal of Applied Clinical Medical Physics; Jul2025, Vol. 26 Issue 7, p1-11, 11p

Closing the gap in plan quality: Leveraging deep‐learning dose prediction for adaptive radiotherapy.

Authors: Domal, Sean J. Maniscalco, Austen Visak, Justin et al.

Source: Journal of Applied Clinical Medical Physics; May2025, Vol. 26 Issue 5, p1-14, 14p

Enhanced dose prediction for head and neck cancer artificial intelligence‐driven radiotherapy based on transfer learning with limited training data.

Authors: Wang, Hui‐Ju Maniscalco, Austen Sher, David et al.

Source: Journal of Applied Clinical Medical Physics; May2025, Vol. 26 Issue 5, p1-12, 12p

Strategies for Offline Adaptive Biology-Guided Radiotherapy (BgRT) on a PET-Linac Platform.

Authors: Cai, Bin Banks, Thomas I. Shen, Chenyang et al.

Source: Cancers. Aug2025, Vol. 17 Issue 15, p2470. 15p.

Assessing population‐based to personalized planning strategies for head and neck adaptive radiotherapy.

Authors: Visak, Justin Liao, Chien‐Yi Zhong, Xinran et al.

Source: Journal of Applied Clinical Medical Physics; Mar2025, Vol. 26 Issue 3, p1-10, 10p

Beyond conventional bounds: Surpassing system limits for stereotactic ablative (SAbR) lung radiotherapy using CBCT‐based adaptive planning system.

Authors: Gonzalez, Yesenia Visak, Justin Overman, Luke et al.

Source: Journal of Applied Clinical Medical Physics; Aug2024, Vol. 25 Issue 8, p1-9, 9p

Simulation-Omitting and Using Library Patients for Pre-Planning Online Adaptive Radiotherapy (SUPPORT): A Feasibility Study for Spine Stereotactic Ablative Radiotherapy (SAbR) Patients.

Authors: Wang, Da Kim, Heejung Zhuang, Tingliang et al.

Source: Cancers. Apr2025, Vol. 17 Issue 7, p1216. 11p.

Physicists should perform reference planning for CBCT guided online adaptive radiotherapy.

Authors: Lin, Mu‐Han Kavanaugh, James A. Kim, Minsun et al.

Source: Journal of Applied Clinical Medical Physics; Oct2023, Vol. 24 Issue 10, p1-7, 7p

Evaluating machine learning enhanced intelligent‐optimization‐engine (IOE) performance for ethos head‐and‐neck (HN) plan generation.

Authors: Visak, Justin Inam, Enobong Meng, Boyu et al.

Source: Journal of Applied Clinical Medical Physics; Jul2023, Vol. 24 Issue 7, p1-10, 10p

Intentional deep overfit learning for patient‐specific dose predictions in adaptive radiotherapy.

Authors: Maniscalco, Austen Liang, Xiao Lin, Mu‐Han et al.

Source: Medical Physics. Sep2023, Vol. 50 Issue 9, p5354-5363. 10p.

Subjects: Deep learning, Medical dosimetry, Adaptive testing, Radiotherapy, Computed tomography, Prediction models

Clinical experience on patient‐specific quality assurance for CBCT‐based online adaptive treatment plan.

Authors: Shen, Chenyang Chen, Liyuan Zhong, Xinran et al.

Source: Journal of Applied Clinical Medical Physics; Apr2023, Vol. 24 Issue 4, p1-6, 6p