MO-DE-201-00: Medical Physics Leadership Academy

2016 ◽  
Vol 43 (6Part29) ◽  
pp. 3697-3697
Author(s):  
Jessica Clements
Keyword(s):  
Medical Physics ◽  
Leadership Academy

Guideline for radioimmunotherapy of rituximab relapsed or refractory CD20+ follicular B-cell nonHodgkin´s lymphoma

2004 ◽  
Vol 43 (05) ◽  
pp. 171-176 ◽  
Author(s):  
T. Behr ◽  
F. Grünwald ◽  
W. H. Knapp ◽  
L. Trümper ◽  
C. von Schilling ◽  
...  
Keyword(s):  
Quality Control ◽  
Quality Management ◽  
Medical Physics ◽  
Essential Elements ◽  
Background Information ◽  
After Care ◽  
Complete Treatment ◽  
Close Cooperation ◽  
Work Up

Summary:This guideline is a prerequisite for the quality management in the treatment of non-Hodgkin-lymphomas using radioimmunotherapy. It is based on an interdisciplinary consensus and contains background information and definitions as well as specified indications and detailed contraindications of treatment. Essential topics are the requirements for institutions performing the therapy. For instance, presence of an expert for medical physics, intense cooperation with all colleagues committed to treatment of lymphomas, and a certificate of instruction in radiochemical labelling and quality control are required. Furthermore, it is specified which patient data have to be available prior to performance of therapy and how the treatment has to be carried out technically. Here, quality control and documentation of labelling are of greatest importance. After treatment, clinical quality control is mandatory (work-up of therapy data and follow-up of patients). Essential elements of follow-up are specified in detail. The complete treatment inclusive after-care has to be realised in close cooperation with those colleagues (haematology-oncology) who propose, in general, radioimmunotherapy under consideration of the development of the disease.

The Solo Practice of Medical Physics in Radiation Oncology

10.37206/80 ◽  
2003 ◽  
Author(s):  
Per H. Halvorsen ◽  
Julie F. Dawson ◽  
Martin W. Fraser ◽  
Geoffrey S. Ibbott ◽  
Bruce R. Thomadsen
Keyword(s):  
Radiation Oncology ◽  
Medical Physics ◽  
Solo Practice

Essentials and Guidelines for Hospital Based Medical Physics Residency Training Programs

10.37206/35 ◽  
1990 ◽  
Author(s):  
Edward S. Sternick ◽  
Richard G. Evans ◽  
E. Roblert Heitzman ◽  
James G. Kereiakes ◽  
Edwin C. McCullough ◽  
...  
Keyword(s):  
Residency Training ◽  
Training Programs ◽  
Medical Physics

Essentials and Guidelines for Clinical Medical Physics Residency Training Programs

10.37206/149 ◽  
2013 ◽  
Author(s):  
Joann Prisciandaro ◽  
Charles Willis ◽  
Jay Burmeister ◽  
Geoffrey Clarke ◽  
Rupak Das ◽  
...  
Keyword(s):  
Residency Training ◽  
Training Programs ◽  
Medical Physics

Top 100 most-cited articles on medical imaging applications of artificial intelligence: a bibliometric analysis (Preprint)

2020 ◽  
Author(s):  
Ying Liu ◽  
Ziyan Yu ◽  
Shuolan Jing ◽  
Honghu Jiang ◽  
Chunxia Wang
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Bibliometric Analysis ◽  
Clinical Medicine ◽  
Medical Physics ◽  
Medical Image Analysis ◽  
The United States ◽  
Independent Learning ◽  
Learning Ability ◽  
Core Technology

BACKGROUND Artificial intelligence (AI) has penetrated into almost every aspect of our lives and is rapidly changing our way of life. Recently, the new generation of AI taking machine learning and particularly deep convolutional neural network theories as the core technology, has stronger learning ability and independent learning evolution ability, combined with a large amount of learning data, breaks through the bottleneck limit of model accuracy, and makes the model efficient use. OBJECTIVE To identify the 100 most cited papers in artificial intelligence in medical imaging, we performed a comprehensive bibliometric analysis basing on the literature search on Web of Science Core Collection (WoSCC). METHODS The 100 top-cited articles published in “AI, Medical imaging” journals were identified using the Science Citation Index Database. The articles were further reviewed, and basic information was collected, including the number of citations, journals, authors, publication year, and field of study. RESULTS The highly cited articles in AI were cited between 72 and 1,554 times. The majority of them were published in three major journals: IEEE Transactions on Medical Imaging, Medical Image Analysis and Medical Physics. The publication year ranged from 2002 to 2019, with 66% published in a three-year period (2016 to 2018). Publications from the United States (56%) were the most heavily cited, followed by those from China (15%) and Netherlands (10%). Radboud University Nijmegen from Netherlands, Harvard Medical School in USA, and The Chinese University of Hong Kong in China produced the highest number of publications (n=6). Computer science (42%), clinical medicine (35%), and engineering (8%) were the most common fields of study. CONCLUSIONS Citation analysis in the field of artificial intelligence in medical imaging reveals interesting information about the topics and trends negotiated by researchers and elucidates which characteristics are required for a paper to attain a “classic” status. Clinical science articles published in highimpact specialized journals are most likely to be cited in the field of artificial intelligence in medical imaging.

scholarly journals Greetings from the new Medical Physics editorial team

2021 ◽  
Vol 48 (1) ◽  
pp. 1-2
Author(s):  
John M. Boone ◽  
Stanley H. Benedict ◽  
Elle Thomas
Keyword(s):  
Medical Physics ◽  
Editorial Team
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