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The aim of this study was to scale structured report templates categorizing actionable renal findings across health systems and create a centralized registry of patient and report data.In January 2017, three academic radiology departments agreed to prospectively include identical structured templates categorizing the malignant likelihood of renal findings in ≥90% of all adult ultrasound, MRI, and CT reports, a new approach for two sites. Between November 20, 2017, and September 30, 2019, deidentified HL7 report data were transmitted to a centralized ACR registry. An automated algorithm extracted categories. Radiologists were requested to addend reports with missing or incomplete templates after the first month. Separately, each site submitted patient sociodemographic and clinical data 12 months before and at least 3 months after enrollment.A total of 164,982 eligible radiology reports were transmitted to the registry; 4,159 (2.5%) were excluded because of missing categories or radiologist names. The final cohort included 160,823 examinations on 102,619 unique patients. Mean template use before and after addendum requests was 99.3% and 99.9% at SITE1, 86.5% and 94.6% at SITE2, and 91.4% and 96.0% at SITE3. Matching patient sociodemographic and clinical data were obtained on 96.9% of reports from SITE1, 94.2% from SITE2, and 96.0% from SITE3. Regulatory, cultural, and technology barriers to the creation of a multisite registry were identified.Barriers to the adoption of unified structured report templates for actionable kidney findings can be addressed. Deidentified report and patient data can be securely transmitted to an external registry. These data can facilitate the collection of diverse evidence-based population imaging outcomes.

إعادة بناء الفك السفلي بعد الصدمة الشديدة ، كدمات أو تشوه هي واحدة من أصعب المشاكل التي تواجهها جراحة الفم والوجه والفكين. الغرض من هذا البحث هو تصميم وتطوير نموذج CAD ثلاثي الأبعاد باستخدام تقنية هندسية عكسية تعتمد على بيانات التصوير الطبي للمريض لإنشاء عملية غرس محاكاة. توفر المنهجية المقترحة في هذا البحث بيئة متكاملة لزراعة الغرسات وتحسين المنتجات. زرع نموذج ملكة جمال جزء تصميم وتحليل باستخدام باستخدام meshmixer. شملت غرس العمل دراسة حالة لرجل يبلغ من العمر 35 عاما مصابا بحادث مرور في الفك السفلي. تم الحصول على بيانات المريض التي تم الحصول عليها من CBCT لتصميم نموذج شبكي للمنطقة المطلوبة. بناء النموذج الطبي النهائي والتكامل بين الزرع والطراز الفك السفلي باستخدام Meshmixer. توضح العمليات والمنهجية إمكانية تصنيع غرس أكثر تخصيصا. يمكن تطبيق النماذج الأولية السريعة وتقنيات الهندسة العكسية في المجال الطبي لتحسين الجراحة والتشخيص والعلاج.

Wireless Mobile Ad-Hoc Networks is one of the attractive research field that growing exponentially in the last decade. it surrounded by much challenges that should be solved the improve establishment of such networks. Failure of wireless link is considered as one of popular challenges faced by Mobile Ad-Hoc Networks (MANETs). As this type of networks does not require any pre-exist hardware. As well as, every node have the ability of roaming where it can be connected to other nodes dynamically. Therefore, the network internal structure will be unpredictably changed frequently according to continuous activities between nodes that simultaneously update network topology in the basis of active ad-hoc nature. This model puts the functionality of routing operation in crucial angle in the area of research under mobile adhoc network field due to highly dynamic nature. Adapting such kernel makes MANET indigence new routing techniques to settle these challenges. Thereafter, tremendous amount of routing protocols proposed to argue with ad-hoc nature. Thus, it is quite difficult to specify which protocols operate efficiently under different mobile ad-hoc scenarios. This paper examines some of the prominent routing protocols that are designed for mobile ad-hoc networks by describing their structures, operations, features and then comparing their various characteristics.

Emerging manifestations of artificial intelligence (AI) have featured prominently in virtually all industries and facets of our lives. Within the radiology literature, AI has shown great promise in improving and augmenting radiologist workflow. In pediatric imaging, while greatest AI inroads have been made in musculoskeletal radiographs, there are certainly opportunities within thoracoabdominal MRI for AI to add significant value. In this paper, we briefly review non-interpretive and interpretive data science, with emphasis on potential avenues for advancement in pediatric body MRI based on similar work in adults. The discussion focuses on MRI image optimization, abdominal organ segmentation, and osseous lesion detection encountered during body MRI in children.

Diversity and Network Coding (DC-NC), which is the synergistic combination of Diversity Coding and Network Coding, was recently introduced to provide near instant link failure recovery and efficient transmission in a wide variety of network architectures. In this paper, DC-NC is applied to a multi-hop Wireless Sensor Network (WSN) and Diversity Coding (DC) is applied within each link in a multi-hop WSN to enable extremely high reliability with very rapid recovery from wireless link/node failures and the loss of data stream(s) at each link and also provide efficient transmission, which are very important metrics for WSNs. Furthermore, the reliability and rapid fault recovery can be extended to broadcasting applications, along with increased throughput.

The synergistic combination of Diversity and Network Coding (DC-NC) was previously introduced to provide very low end-to-end latency in recovering from a link failure and improve the throughput for a wide variety of network architectures. This paper is directed towards further improving DC-NC to be able to tolerate multiple, simultaneous link failures with less computational complexity. In this way, reliability will be maximized and the recovery time from multiple link or node failures is reduced in 5G fronthaul wireless networks. This is accomplished by modifying Triangular Network Coding (TNC) to create enhanced DC-NC (eDC-NC) that is applied to 5G wireless Fog computing-based Radio Access Networks (Fog-RAN). Our results show that using eDC-NC coding in Fog-RAN fronthaul network will provide ultra-reliability and enable near-instantaneous fault recovery while retaining the throughput improvement feature of DC-NC. In addition, the scalability of eDC-NC coding is demonstrated. Furthermore, it is shown that the redundancy percentage for complete protection is always less than 50% for the practical cases that were evaluated.

Enhanced Diversity and Network Coding (eDC-NC), the synergistic combination of Diversity and modified Triangular Network Coding, was introduced recently to provide efficient and ultra-reliable networking with near-instantaneous fault recovery. In this paper it is shown that eDC-NC technology can efficiently and securely broadcast messages in 5G wireless fog-computing-based Radio Access Networks (F-RAN). In particular, this work is directed towards demonstrating the ability of eDC-NC technology to more efficiently provide secure messages broadcasting than standardized methods such as Secure Multicasting using Secret (Shared) Key Cryptography, such that the adversary has no ability to acquire information even if they wiretap the entire F-RAN network (except of course the source and destination nodes). Our results show that using secure eDC-NC technology in F-RAN fronthaul network will enhance secure broadcasting and provide ultra-reliability networking, near-instantaneous fault recovery, and retain the throughput benefits of Network Coding., 12 pages, 8 figures

Rapid recovery from link failures was previously demonstrated via the synergistic combination of Diversity and Network Coding (DC-NC) for a wide variety of network architectures. In this paper, the DC-NC methodology is further enhanced to achieve near-instant recovery from multiple, simultaneous wireless link failures by modifying Triangular Network Coding (TNC) to create enhanced DC-NC (eDC-NC) that is applied to 5G wireless Fog computing based Radio Access Networks (F-RANs). In addition, an explicit algorithm for the eDC-NC decoding process is provided. Our results demonstrate that applying eDC-NC coding to a F-RAN fronthaul network will provide ultra-reliability, enable near-instantaneous fault recovery, and enhance the throughput by at least 20% (for three broadcasted data streams).

Very fast link failure recovery and high throughput can be achieved via the synergistic combination of Diversity and Network Coding (DC-NC), an open-loop coding technique, in a wide variety of network architectures. In this paper, DC-NC is applied to enable recovering from a wireless link/node failure in the fronthaul portion of downlink Coordinated Multi Point (CoMP) 5G wireless network in a C-RAN environment. Our results demonstrate that by utilizing DC-NC coding in CoMP systems, resource consumption is reduced by about one-third and ultra-reliability with near-instantaneous fault recovery is achieved.

Near instant link failure recovery and lower energy consumption can be achieved via the synergistic combination of Diversity and modified Triangular Network Coding (eDC-NC), an open-loop coding technique, in a wide variety of network architectures. In this paper, eDC-NC is applied to Wireless Sensor Networks (WSNs) to enable very rapid recovering from wireless link/node failures and provide low computational and energy cost, which are very important metrics for WSNs. It is shown that utilizing eDC-NC coding in WSNs can provide ultra-reliability with very rapid fault recovery, decrease energy consumption, and increase the network throughput for broadcasting applications.

This paper presents a robust solution for link and node failures in network function virtualization for 5G and beyond system. Namely, the synergistic combination of Diversity and Network Coding schemes is leveraged here for robust link failure recovery. The scheme offers near-instantaneous packet recovery without feedback requests with enhanced throughput. Hence, it eliminates latency associated with retransmissions and rerouting by using error control across spatially diverse paths.

This paper is directed towards improving both throughput and reliability of 5G wireless Cloud Radio Access Networks (C-RANs) by the synergistic combination of Diversity Coding and Network Coding (DC-NC). In this paper, we directly apply the concept of DC-NC coding to two network scenarios: first, remote radio heads in a CRAN connected to the baseband unit in two hierarchical tiers with optical and wireless fronthaul links, second, most remote radio heads are connected directly to the baseband unit via wireless links. Our results show that the combination of Diversity and Network Coding increases the throughput of fronthaul networks for downlink broadcasting or multicasting applications, while enabling reliable networking with near-instant latency in fault recovery by using forward error control across spatially diverse paths. Moreover, the number of redundant links inherent in Diversity Coding can be decreased using the proposed scheme.

In this paper we study the application of Diversity Coding to enable near-instantaneous recovery from link failures in 5G Centralized Radio Access Network (C-RAN) networks. We focus on networks where remote radio heads in a C-RAN are connected to the baseband unit with wireless fronthaul links. In order to avoid retransmissions and rerouting delays due to link failures, we investigate use Diversity Coding where a feedforward network design uses forward error control across spatially diverse paths to enable reliable networking with minimal delay.

In this paper we study the application of Diversity Coding to enable near-instantaneous recovery from link failures in 5G wireless Cloud Radio Access Network (C-RAN) networks. We focus on networks where remote radio heads in a C-RAN are connected to the baseband unit in two hierarchical tiers with optical and wireless fronthaul links. In order to avoid retransmissions and re-routing delays due to link failures in wireless links, we investigate the use Diversity Coding where a feed-forward network design uses forward error control across spatially diverse paths to enable reliable networking with minimal delay.

Neuroblastoma (NB) is the most common extra-cranial solid tumor in children and the most common malignancy in infants, with complete resection being curative in low-stage disease. The previous standard of treatment for many abdominal NBs involving the adrenal gland had been open surgery; however, there have been numerous descriptions of the safety and feasibility of a laparoscopic approach to resect adrenal masses in the pediatric population in benign and malignant disease, including improved cosmetic results, decreased length of stay, decreased surgical morbidity, and comparable oncological outcomes to open surgery. Despite these reported advantages over open surgery, the newer robot-assisted laparoscopy (RAL) offers benefits over the conventional laparoscopic approach that could further improve outcomes and expand the use of minimally invasive surgical approaches for pediatric adrenal masses. RAL offers many additional advantages over conventional laparoscopy, such as 3D visualization, increased range of motion of surgical instruments, tremor control, and a shorter learning curve compared with traditional laparoscopic surgery, while still maintaining the advantages of minimally invasive surgery. The body of literature concerning robot-assisted oncological surgery involving the adrenal gland in children is quite small, and to our knowledge no case reports have been published describing robot-assisted removal of an adrenal NB in a pediatric patient. We present our experience and technique of an RAL approach for lymph-node dissection and radical resection of a low-stage NB involving the adrenal gland with no image-defined risk factors in a 15-month-old infant.