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JournalQ1· SCImago 2025

Medical Physics

ISSN 0094-2405

• Q1Quartile
• 229h-index
• 11papers summarised

About this journal

Medical Physics is a Q1 journal by SCImago Journal Rank (2025 data) and an h-index of 229. Most of its papers in the Pofolia pool fall under Radiation. Pofolia holds AI summaries of 11 paper(s) from this journal; the most cited is “Tolerance limits and methodologies for<scp>IMRT</scp>measurement‐based…” (1067 citations).

The quartile (Q1–Q4) is the journal's percentile position within its subject area by SCImago Journal Rank; Q1 is the top 25%. What is a Q1 journal?

Papers we summarise from this journal

• Tolerance limits and methodologies for<scp>IMRT</scp>measurement‐based verification<scp>QA</scp>:<i>Recommendations of<scp>AAPM</scp>Task Group No. 218</i>2018 · 1067 citations
• Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 1322017 · 849 citations
• The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management2016 · 538 citations
• A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications2014 · 538 citations
• AnatomyNet: Deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy2018 · 529 citations
• Report of the Task Group 186 on model‐based dose calculation methods in brachytherapy beyond the TG‐43 formalism: Current status and recommendations for clinical implementation2012 · 527 citations
• Segmentation of organs‐at‐risks in head and neck <scp>CT</scp> images using convolutional neural networks2016 · 506 citations
• An efficient protocol for radiochromic film dosimetry combining calibration and measurement in a single scan2012 · 394 citations
• The Physics of Radiation Therapy2015 · 388 citations
• Predicting dose‐volume histograms for organs‐at‐risk in IMRT planning2012 · 385 citations
• Automatic treatment planning based on three‐dimensional dose distribution predicted from deep learning technique2018 · 365 citations

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