Radiation therapy dose prediction for left-sided breast cancers using two-dimensional and three-dimensional deep learning models.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)

PMID: 33756222

Abstract

PURPOSE: To develop a deep learning model capable of producing clinically acceptable dose distributions for left-sided breast cancers for 3D-CRT while exploring the use of two-dimensional versus three-dimensional anatomical data.

Authors

Natasha Hedden

Department of Physics, Ryerson University, Toronto, ON, Canada; Department of Medical Physics, Walker Family Cancer Centre, St. Catharines, ON, Canada. Electronic address: natasha.hedden@ryerson.ca.
Heping Xu

Department of Medical Physics, Walker Family Cancer Centre, St. Catharines, ON, Canada.

Keywords

Breast Neoplasms Deep Learning Female Humans Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Unilateral Breast Neoplasms

External Resources

View on PubMed Access via DOI PubMed (33756222)

Radiation therapy dose prediction for left-sided breast cancers using two-dimensional and three-dimensional deep learning models.

Abstract

Authors

Keywords

External Resources

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