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PURPOSE: This study aimed to determine the viability of focal dose escalation to prostate cancer intraprostatic lesions (IPLs) from multiparametric magnetic resonance (mpMRI) and prostate-specific membrane antigen positron emission tomography (PSMA-PET) images using high-dose-rate (HDR) prostate brachytherapy (pBT). METHODS AND MATERIALS: Retrospective data from 20 patients treated with HDR pBT was utilized. The interobserver contouring variability of 5 observers was quantified using the dice similarity coefficient (DSC) and mean distance to agreement (MDA). Uncertainty in propagating IPL cont...

Objectives: The objective of this study was to assess the repeatability of MRI for the purpose of radiotherapy treatment planning by considering the difference in registering MRI to MRI compared to registering CT and MRI. Methods: Fifty patients undergoing radiotherapy planning for gynaecological, prostate, rectal, head and neck and CNS malignancies had a planning CT followed by two T2-weighted MRIs. Anatomical landmarks were contoured on each dataset and the images were rigidly registered. Centre of Mass (COM), Dice Similarity Coefficient (DSC), and Mean Distance to Agreement (MDA) were calcu...

Six University of Kentucky students ranked among the top scorers for research presentations given at the Kentucky Academy of Science’s 2022 Annual Meeting in November.

Corista-Led Study Shows Potential to Improve Renal Biopsy Analysis Share Article Journal of Pathology Informatics Editorial Calls Concept “Sound” and Results “Encouraging” Journal of Pathology Informatics Editorial calls Corista-led study on use of AI and machine learning for renal biopsy analysis “Sound” and Results “Encouraging” CONCORD, Mass. (PRWEB) June 09, 2021 A Corista-led study on the impact of applying artificial intelligence to the workflow of a Renal Pathologist and how this might ease and improve th...

Existing approaches for SAR image registration focus on the global transformation correction between SAR images. However, there are often local deformations between images. Due to the time-changing viewpoint of video SAR, the images suffer a lot from local deformations, which can result in false alarms in moving target detection. This article presents an unsupervised image registration approach for the use of video SAR moving target detection, which has good registration performance and acceptable processing efficiency. The designed unsupervised learning-based framework is a cascade of two con...