Automatic multi‐catheter detection using deeply supervised convolutional neural network in MRI‐guided HDR prostate brachytherapy
Abstract
High‐dose‐rate (HDR) brachytherapy is an established technique to be used as monotherapy option or focal boost in conjunction with external beam radiation therapy (EBRT) for treating prostate cancer. Radiation source path reconstruction is a critical procedure in HDR treatment planning. Manually identifying the source path is labor intensive and time inefficient. In recent years, magnetic resonance imaging (MRI) has become a valuable imaging modality for image‐guided HDR prostate brachytherapy due to its superb soft‐tissue contrast for target delineation and normal tissue contouring. The purpose of this study is to investigate a deep‐learning‐based method to automatically reconstruct multiple catheters in MRI for prostate cancer HDR brachytherapy treatment planning.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jun 15, 2020
- Source ID
- 10.1002/mp.14307
Entities
People
- Pretesh Patel
- Richard L.j. Qiu
- Sean A. Dresser
- Tian Liu
- Tonghe Wang
- Walter J. Curran
- Xianjin Dai
- Xiaofeng Yang
- Yang Lei
- Yupei Zhang
Organizations
- Emory University
- National Cancer Institute
- United States Department of Defense