Electronic Elections 2018
Dear ESR Members,
Our beloved European Society of Radiology (ESR) is truly experiencing an Annus Mirabilis, a blessed year, a wonderful year, a miraculous year. After an all-time high in ECR 2017 participation a new membership record at the end of November 2017, and ECR 2018 set to break new records, I am happy and proud to announce that with this year's electronic elections we reached another milestone in terms of candidates and participation.
In November 2017, the ESR Executive Council nominated 3 candidates for the position of the 2nd Vice-President and 3 candidates for the position of the ESR Education Committee Chair. This is an unprecedented luxury: 6 highly valuable candidates willing to stand for office, to serve the society and the radiological community at large. And, the ESR election stirred great interest among our members, with an unmatched record of 4,598 votes cast.
But, I’m sure that you are all anxious to see the results, so here they come.
The following officers have been elected:
ESR 2nd Vice-President: Michael Fuchsjäger (AT)
ESR Education Committee Chair: Carlo Catalano (IT)
A big thank you to all ESR Full Members for casting your vote and contributing to an all-time turnout of 15 percent!
Elections and candidates prepared to stand for office are the lifeblood of any society. It gives me great pleasure to note that the ESR is a healthy, vibrant and thriving society, with committed and motivated members.
On behalf of all of us in the ESR, I offer my sincere and heartfelt congratulations to the election winners. But, at the same time, let me say that, in this election, there are no losers, but only winners, as we all are part of one big community!
Thank you very much for your confidence and your support and long live the ESR.
Prof. dr. Paul M. Parizel
Chair of the ESR Board of DirectorsAdd a comment
Electronic Elections 2018
Voting period: January 15-28, 2018
All ESR Full Members are entitled to vote and will receive a personal invitation via e-mail to participate in this year's electronic elections.
• ESR 2nd Vice-President
Christoph D. Becker Geneva / CH
Michael Fuchsjäger Graz / AT
Laura Oleaga Barcelona / ES
• ESR Education Committee Chair
Carlo Catalano Rome / IT
William H. Ramsden Leeds / UK
Jacob Sosna Jerusalem / ILAdd a comment
source: National Institute of Health
The NIH Clinical Center recently released over 100,000 anonymized chest x-ray images and their corresponding data to the scientific community. The release will allow researchers across the country and around the world to freely access the datasets and increase their ability to teach computers how to detect and diagnose disease. Ultimately, this artificial intelligence mechanism can lead to clinicians making better diagnostic decisions for patients.
NIH compiled the dataset of scans from more than 30,000 patients, including many with advanced lung disease. Patients at the NIH Clinical Center, the nation’s largest hospital devoted entirely to clinical research, are partners in research and voluntarily enroll to participate in clinical trials. With patient privacy being paramount, the dataset was rigorously screened to remove all personally identifiable information before release.
Reading and diagnosing chest x-ray images may be a relatively simple task for radiologists but, in fact, it is a complex reasoning problem which often requires careful observation and knowledge of anatomical principles, physiology and pathology. Such factors increase the difficulty of developing a consistent and automated technique for reading chest X-ray images while simultaneously considering all common thoracic diseases.
By using this free dataset, the hope is that academic and research institutions across the country will be able to teach a computer to read and process extremely large amounts of scans, to confirm the results radiologists have found and potentially identify other findings that may have been overlooked.
In addition, this advanced computer technology may also be able to:
- help identify slow changes occurring over the course of multiple chest x-rays that might otherwise be overlooked
- benefit patients in developing countries that do not have access to radiologists to read their chest x-rays, and
- create a virtual radiology resident that can later be taught to read more complex images like CT and MRI in the future.
With an ongoing commitment to data sharing, the NIH research hospital anticipates adding a large dataset of CT scans to be made available as well in the coming months.
Wang X, Peng Y, Lu L, Lu Z, Bagheri M, Summers RM. ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases. IEEE CVPR 2017, http://openaccess.thecvf.com/content_cvpr_2017/papers/Wang_ChestX-ray8_Hospital-Scale_Chest_CVPR_2017_paper.pdf(link is external)
Images are available via Box: https://nihcc.app.box.com/v/ChestXray-NIHCC(link is external)
Ronald M. Summers, M.D., Ph.D., Senior Investigator of the Clinical Image Processing Service in the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory of the NIH Clinical Center Radiology and Imaging Sciences Department is available for interviews.
About the NIH Clinical Center: The NIH Clinical Center is the clinical research hospital for the National Institutes of Health. Through clinical research, clinician-investigators translate laboratory discoveries into better treatments, therapies and interventions to improve the nation's health. More information: https://clinicalcenter.nih.gov.
About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov.Add a comment