Development and clinical implementation of SeedNet: A sliding-window convolutional neural network for radioactive seed identification in MRI-assisted radiosurgery (MARS).
Jeremiah W SandersSteven J FrankRajat J KudchadkerTeresa L BrunoJingfei MaPublished in: Magnetic resonance in medicine (2019)
SeedNet can be used to perform automated radioactive seed identification in prostate MRI after LDR brachytherapy. Image quality improvement through pulse sequence optimization is expected to improve SeedNet's performance when imaging without an ERC.
Keyphrases
- deep learning
- convolutional neural network
- quality improvement
- contrast enhanced
- magnetic resonance imaging
- prostate cancer
- high dose
- high resolution
- radiation therapy
- bioinformatics analysis
- primary care
- blood pressure
- patient safety
- machine learning
- healthcare
- brain metastases
- computed tomography
- benign prostatic hyperplasia
- low dose
- photodynamic therapy
- rectal cancer