Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data - Gsaxner, Christina; Roth, Peter M.; Wallner, Jürgen; Egger, Jan (PloS one, 2019)
Keywords: Algorithms; Artificial neural networks; Biology and Life Sciences; Biomedical engineering; Bladder; Bladder cancer; Bladder diseases; Cancer therapies; CAT scans; Chen, George; Computed tomography; Computer and Information Sciences; Computer graphics; Computer science; Data augmentation; Data mining; Deep Learning; Diagnosis; Diagnostic imaging; Drug dosages; Emissions; Ground truth; Humans; Image analysis; Image processing; Image Processing, Computer-Assisted; Image segmentation; International conferences; Laboratories; Learning algorithms; Maxillofacial surgery; Medical imaging; Medical imaging equipment; Medical treatment; Medicine; Medicine and Health Sciences; Neural networks; Pattern recognition; Positron emission; Positron emission tomography; Prostate cancer; Radiation therapy; Research and Analysis Methods; Semantics; Surgery; Tomography; Tomography, X-Ray Computed; Trade agreements; Training; Urinary bladder; Urinary Bladder - diagnostic imaging; Austria