Rapid in vivo EPID image prediction using a combination of analytically calculated attenuation and AI predicted scatter.

Background: The electronic portal imaging device (EPID) can be used in vivo, to detect on-treatment errors by evaluating radiation exiting a patient. To detect deviations from the planning intent, image predictions need to be modeled based on the patient's anatomy and plan information. To date in vivo transit images have been predicted using Monte Carlo (MC) algorithms.

Improving 3D dose prediction for breast radiotherapy using novel glowing masks and gradient-weighted loss functions.

Background: The quality of treatment plans for breast cancer can vary greatly. This variation could be reduced by using dose prediction to automate treatment planning. Our work investigates novel methods for training deep-learning models that are capable of producing high-quality dose predictions for breast cancer treatment planning.

Neural network dose prediction for cervical brachytherapy: Overcoming data scarcity for applicator-specific models.

Background: 3D neural network dose predictions are useful for automating brachytherapy (BT) treatment planning for cervical cancer. Cervical BT can be delivered with numerous applicators, which necessitates developing models that generalize to multiple applicator types. The variability and scarcity of data for any given applicator type poses challenges for deep learning.

Automated treatment planning framework for brachytherapy of cervical cancer using 3D dose predictions.

. To lay the foundation for automated knowledge-based brachytherapy treatment planning using 3D dose estimations, we describe an optimization framework to convert brachytherapy dose distributions directly into dwell times (DTs)..

Trait self-focused attention increases sensitivity to nonconscious primes: evidence from effort-related cardiovascular reactivity.

A broad range of primes presented outside of awareness - ranging from emotional faces to people's first names - can influence the physiological mobilization of effort during active coping tasks. Who responds more strongly to implicit cues? Based on models of self-awareness, the present research examined how individual differences in self-focused attention influence sensitivity to nonconscious primes. Adults completed a challenging cognitive task in which two kinds of primes were presented (people's first names and words related to the task's difficulty).