Swanson Pridgen (alibitrunk28)

Accurate segmentation of organs-at-risk is important inprostate cancer radiation therapy planning. However, poor soft tissue contrast in CT makes the segmentation task very challenging. We propose a deep convolutional neural network approach to automatically segment the prostate, bladder, and rectum from pelvic CT. A hierarchical coarse-to-fine segmentation strategy is used where the first step generates a coarse segmentation from which an organ-specific region of interest (ROI) localization map is produced. The second step produces detailed and accurate segmentation of the organs. The ROI localization map is generated using a 3D U-net. The localization map helps adjusting the ROI of each organ that needs to be segmented and hence improves computational efficiency by eliminating irrelevant background information. For the fine segmentation step, we designed a fully convolutional network (FCN) by combining a generative adversarial network (GAN) with a U-net. Specifically, the generator is a 3D U-net that is trained to predict individual pelvic structures, and the discriminator is an FCN which fine-tunes the generator predicted segmentation map by comparing it with the ground truth. The network was trained using 100 CT datasets and tested on 15 datasets to segment the prostate, bladder and rectum. The average Dice similarity (mean±SD) of the prostate, bladder and rectum are 0.90±0.05, 0.96±0.06 and 0.91±0.09, respectively, and Hausdorff distances of these three structures are 5.21±1.17, 4.37±0.56 and 6.11±1.47(mm), respectively. The proposed method produces accurate and reproducible segmentation of pelvic structures, which can be potentially valuable for prostate cancer radiotherapy treatment planning.Inconsistencies exist regarding the relation between physical activity (PA) and internalizing symptomology in early adolescence, and there is need for investigation of potential moderators that may account for these discrepancies. The current study utilized a Self-Determination Theory Framework to investigate the main effects of five key motivations to exercise and their moderating effects between PA and internalizing problems in an underserved sample of adolescents (n = 167; mean age = 12.19 years; 73% African American). Analyses showed that intrinsic motivations were negatively related to internalizing problems and extrinsic motivations were positively related. WNK463 PA was only protective against internalizing problems when intrinsic motivations were high and had iatrogenic effects when these were low. Exploratory analyses further delineated the unique effects of motivational orientations. Clinical implications and future research directions are discussed.Quarantine conditions arising as a result of the coronavirus (COVID-19) have had a significant impact on global production-rates and supply chains. This has coincided with increased demands for medical and personal protective equipment such as face shields. Shortages have been particularly prevalent in western countries which typically rely upon global supply chains to obtain these types of device from low-cost economies. National calls for the repurposing of domestic mass-production facilities have the potential to meet medical requirements in coming weeks, however the immediate demand associated with the virus has led to the mobilisation of a diverse distributed workforce. Selection of appropriate manufacturing processes and underused supply chains is paramount to the success of these operations. A simplified medical face shield design is presented which repurposes an assortment of existing alternative supply chains. The device is easy to produce with minimal equipment and training. It is hoped that the methodology and approach presented is of use to the wider community at this critical time. © 2020 The Authors. Published by Elsevier Ltd.We revisit staircases for words and prove several exact as well as asymptotic results for longest left-most staircase subsequences and s