Automatic deep learning based quality assessment of transperineal ultrasound guided prostate radiotherapy

Saskia M. Camps, Tim Houben, Christopher Edwards, Maria Antico, Matteo Dunnhofer, Esther Martens, Jose Baeza, Ben G.L. Vanneste, Evert Van Limbergen, Peter H.N. de With, Frank J.W. Verhaegen, Gustavo Carneiro, D. Fontanarosa

Research output: Contribution to journalConference articlepeer-review

Abstract

Ultrasound (US) is one of the imaging modalities that can be used for image‐guided radiotherapy (RT) workflows of prostate cancer patients. It allows real‐time volumetric tracking during the course of the RT treatment, which could potentially improve the precision of radiation dose delivery. However, intra‐fraction motion management using US image guidance is not yet widespread. This can be partially attributed to the need for image interpretation by a trained operator during or after US image acquisition.
Original languageEnglish
JournalJournal of Medical Radiation Sciences
Volume66
Issue numberS1
DOIs
Publication statusPublished - 29 Mar 2019
EventASMIRT / AACRT 2019 International Conference - Adelaide, Australia
Duration: 28 Mar 201931 Mar 2019

Fingerprint

Dive into the research topics of 'Automatic deep learning based quality assessment of transperineal ultrasound guided prostate radiotherapy'. Together they form a unique fingerprint.

Cite this