Publications by authors named "F D Brooks"

Food insecurity is an indicator of well-being in the United States. A high proportion of recipients of charitable food assistance (CFA) are women and are often in charge of specific household managerial responsibilities (e.g.

View Article and Find Full Text PDF

Background: The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report.

Purpose: The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain-relevant assessments via the analysis of relevant image statistics.

Methods: As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis.

View Article and Find Full Text PDF

Purpose: The Imaging Radiation Oncology Core (IROC) head and neck (H&N) phantom is used to credential institutions for intensity modulated radiation therapy delivery for all anatomic sites where delivery of modulated therapy is a primary challenge. This study evaluated how appropriate the use of this phantom is for varied clinical anatomy by evaluating how closely the IROC H&N phantom described clinical dose errors from beam modeling compared with various anatomic sites.

Methods And Materials: The multileaf collimator (MLC) offset, transmission, percent depth dose, and 7 additional beam modeling parameters for a Varian accelerator were modified in RayStation to match community data at the 2.

View Article and Find Full Text PDF

Brown root rot disease (BRRD) is a highly destructive tree disease. Early diagnosis of BRRD has been challenging because the first symptoms and signs are often observed after extensive tissue colonization. Existing molecular detection methods, all based on the internal transcribed spacer (ITS) region, were developed without testing against global isolates, other wood-decay fungi, or host plant tissues.

View Article and Find Full Text PDF

Diffusion models have emerged as a popular family of deep generative models (DGMs). In the literature, it has been claimed that one class of diffusion models-denoising diffusion probabilistic models (DDPMs)-demonstrate superior image synthesis performance as compared to generative adversarial networks (GANs). To date, these claims have been evaluated using either ensemble-based methods designed for natural images, or conventional measures of image quality such as structural similarity.

View Article and Find Full Text PDF