Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …

Data augmentation involves artificially expanding a dataset by applying various
transformations to the existing data. Recent developments in deep learning have advanced …

Radiopharmaceutical therapy (RPT) is a rapidly develo** field of nuclear medicine, with
several RPTs already well established in the treatment of several different types of cancers …

Abstract Background and Objective: Image-guided clinical diagnosis can be achieved by
automatically and accurately segmenting prostate and prostatic cancer in male pelvic …

Automatic detection and characterization of cancer are important clinical needs to optimize
early treatment. We developed a deep, semisupervised transfer learning approach for fully …

Background Prostate-specific membrane antigen (PSMA) PET/CT imaging is widely used for
quantitative image analysis, especially in radioligand therapy (RLT) for metastatic castration …

Background and objective Training convolutional neural networks based on large amount of
labeled data has made great progress in the field of image segmentation. However, in …

Pretherapy dosimetry prediction is a prerequisite for treatment planning and personalized
optimization of the emerging radiopharmaceutical therapy (RPT). Physiologically based …

Uptake segmentation and classification on PSMA PET/CT are important for automating
whole-body tumor burden determinations. We developed and evaluated an automated deep …

High-resolution intraoperative PET/CT specimen imaging, coupled with prostate-specific
membrane antigen (PSMA) molecular targeting, holds great potential for the rapid ex vivo …