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Email

katrina.woodford@unimelb.edu.au

Credentials


Position
Honorary (Senior Fellow)
The Sir Peter MacCallum Department of Oncology
ORCID

0009-0009-9411-153X

Dr Katrina Woodford

Honorary (Senior Fellow)
The Sir Peter MacCallum Department of Oncology

41 Scholarly works
0 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Version upgrades in treatment planning Systems affect clinical application of a multi-Centre knowledge-based planning model
    DOI: 10.1016/j.tipsro.2026.100417
  • 2026

    Journal article

    Stereotactic Ablative Radiotherapy (SABR) one stop service for lung cancer: A pilot study for early-stage Non-Small-Cell Lung Cancer (NSCLC)
    DOI: 10.1016/j.radonc.2026.111553
  • 2026

    Journal article

    Streamlining Paediatric Palliative Radiotherapy: A Case Study on Reducing Procedural Burden and Avoiding General Anaesthesia Using a Simulation-Free Radiotherapy (SF-RT) Protocol
    DOI: 10.1002/jmrs.70074
  • 2026

    Journal article

    A deep learning approach for predicting linear accelerator output settings in automated radiotherapy planning of oligometastatic cancer
    DOI: 10.1016/j.phro.2025.100890
  • 2025

    Journal article

    Single- versus multi-model in the deep learning prediction of monitor units per control point for automated treatment planning in prostate cancer
    DOI: 10.1002/acm2.70229
  • 2025

    Conference Proceedings

    Machine Output Settings Prediction for Volumetric Modulated Arc Therapy Artificial Intelligence Treatment Planning of Small Tumors in the Lung
    DOI: 10.1016/j.ijrobp.2025.06.3351
  • 2025

    Conference Proceedings

    TCP and NTCP for the Next Generation in Modulated Arc Therapy for Nasopharyngeal Carcinoma
    DOI: 10.1016/j.ijrobp.2025.06.3522
Katrina Woodford

RECENT SCHOLARLY WORKS

  • 2025

    Journal article

    Reirradiation: Evaluation of the occurrence and type in cancer treatment for lung – 2024
    DOI: 10.1016/j.tipsro.2025.100337
  • 2025

    Journal article

    3240 SABR One Stop Service for early lung cancer: same-day sim-plan-and-treat single fraction stereotactic ablative radiotherapy
    DOI: 10.1016/s0167-8140(25)01575-0
  • 2025

    Journal article

    3233 Combining different metastatic anatomical locations for the deep learning prediction of the monitor units per control point
    DOI: 10.1016/s0167-8140(25)01568-3

Acknowledgement of Country

We acknowledge Aboriginal and Torres Strait Islander people as the Traditional Owners of the unceded lands on which we work, learn and live. We pay respect to Elders past, present and future, and acknowledge the importance of Indigenous knowledge in the Academy.

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