Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning

Arterial spin labeling (ASL) imaging is a powerful magnetic resonance imaging technique that allows to quantitatively measure blood perfusion non-invasively, which has great potential for assessing tissue viability in various clinical settings. However, the clinical applications of ASL are currently limited by its low signal-to-noise ratio (SNR), limited spatial resolution, and long imaging time. In this work, we propose an unsupervised deep learning-based image denoising and reconstruction framework to improve the SNR and accelerate the imaging speed of high resolution ASL imaging. The unique feature of the proposed framework is that it does not require any prior training pairs but only the subject's own anatomical prior, such as T1-weighted images, as network input. The neural network was trained from scratch in the denoising or reconstruction process, with noisy images or sparely sampled k-space data as training labels. Performance of the proposed method was evaluated using in vivo experiment data obtained from 3 healthy subjects on a 3T MR scanner, using ASL images acquired with 44-min acquisition time as the ground truth. Both qualitative and quantitative analyses demonstrate the superior performance of the proposed txtc framework over the reference methods. In summary, our proposed unsupervised deep learning-based denoising and reconstruction framework can improve the image quality and accelerate the imaging speed of ASL imaging.     

姜良铎通降腑气的用药经验

姜良铎师从国医大师张学文和著名中医学家董建华,声誉杏林,具有深厚的理论功底和丰富地临床经验。姜良铎善治内科杂病,倡调畅三焦气机,重脏腑协调平衡,尤擅用通降之品化裁于方中,在临床实践中,应用该理论灵活选方用药并注重随证加减,取得良好的治疗效果。     

Formative Research for an Innovative Smartphone Application to Improve Distribution of Healthy Foods to Corner Stores in Baltimore City

We sought to collect information about the operations of wholesalers and store owner perceptions of smartphones to plan for and create a smartphone application that will facilitate the distribution of healthy foods to corner stores. In-depth interviews were conducted with wholesalers, corner store owners, distributors, and food environment experts in Baltimore City, Maryland, which included providing feedback for a mockup of the app. Store owners that were comfortable with smartphones liked the idea of the app because it was economically practical, culturally suitable, simple and easy to use, and provided a large variety of items at a fair or low price. We found that barriers to uptake among corner store owners would be high delivery costs, no foreign language capability, and a complicated user interface. This work will inform future projects that will utilize mHealth technology to improve distribution of healthier foods in food deserts.     

Wireless Connectivity for People with Hearing Loss: Smartphones and Hearing Loss: There's an App for That!

Smartphone use has become increasingly prevalent and patients are frequently using this technology to engage in health-related activities. There are a variety of smartphone applications that can be used to assist individuals with hearing loss, particularly during extreme situations such as a global pandemic which results in restricted face-to-face interactions. The hearing-related applications can be divided into four categories: (1) screening and assessment, (2) intervention and rehabilitation, (3) education and information, and (4) assistive tools. Several subcategories of applications in the assistive tools category are described that may be of interest to individuals with hearing loss, whether they wear hearing aids or not. Examples of the apps along with links are included for each subcategory.     

Smartphone applications available to pregnant women in the United Kingdom: An assessment of nutritional information

The importance of diet during pregnancy is critically important for the short‐ and long‐term health of both mother and child. The number of apps targeting pregnant women is rapidly increasing, yet the nutritional content of these tools remains largely unexplored. This review aimed to evaluate the coverage and content of nutrition information in smartphone apps available to U.K. pregnant women. Keyword searches were conducted in iTunes and Google Play stores in November 2018. Candidate apps were included if they targeted pregnant women, provided pregnancy‐specific nutritional information, had a user rating of at least 4+ based on at least 20 ratings, and were available in English. Nutritional content was assessed for accuracy against U.K. recommendations. Behaviour change techniques (BCTs) were also evaluated. Twenty‐nine apps were included, seven of which originated in the United Kingdom. There was a large variability in the quality of smartphone app nutritional information. The accuracy of nutrition information varied, and several apps conveyed inappropriate information for pregnancy. On average, 10 BCTs were identified per app (range 2–15). Overall, smartphone apps do not consistently provide accurate and useful nutritional information to pregnant women. This study highlights the need for the integration of evidence‐based nutritional information during app development and for increased regulatory oversight. App developers should also make it clear that nutritional content is intended for a specific geographical region or population or modify for the intended audience. These are important considerations for the design of future apps, which are increasingly used to complement existing maternity services.