各企事业单位、高等院校及科研院所：
In recent years, with the development of medical image informatics, mining image features and analyzing clinical information from medical images has gradually attracted the attention of experts in the medical field. Many studies have found that through in-depth mining of image data features, medical images can provide more information that cannot be recognized by the naked eye, which can be used to guide clinical decision-making. In 2012, inspired by the high-yield "omics" concept in the field of biomedicine, Lambin et al. in the Netherlands first proposed the concept of radiomics (radiomics), that is, using computer software to automatically extract massive image quantitative features from image images. Big data analysis means to analyze clinical information, used for tumor characterization, grading and staging, gene analysis, curative effect evaluation and prognosis prediction, etc., to guide and optimize clinical decision-making, and finally realize precision medicine.
The radiomics analysis process mainly includes: image acquisition, lesion segmentation, feature extraction and screening, model construction and clinical information analysis, etc.; its research involves medical and engineering interdisciplinary subjects, requiring close cooperation between medicine and engineering, and most medical students or doctors There is no engineering background, so the "Radiomics Technology and Application Seminar" is specially held for this purpose. This time, the cutting-edge radiomics methods and applications were comprehensively explained, and at the same time, in-depth case studies were conducted to help students master and use radiomics to carry out specific work.
1. Training objectives:
1. Understand the research process and methods of radiomics;
2. Master the writing ideas of radiomics SCI papers;
3. Commonly used radiomics modeling methods;
4. Future development direction and scientific research ideas of radiomics.
2. Lecturers:
Senior experts from Chinese Academy of Sciences, Tsinghua University, Peking University and other scientific research institutions and universities, have rich scientific research experience, and have long been engaged in the teaching of artificial intelligence algorithms such as radiomics, medical image data analysis, machine learning & deep learning Work with research.
3. Time and place:
May 27, 2021-May 30, 2021 Beijing
4. Participants:
All provinces, municipalities and autonomous regions are engaged in health check-ups, disease prevention, disease screening, early diagnosis, disease assessment, treatment selection, rehabilitation curative effect evaluation, grading diagnosis and treatment, etc. master's and doctoral candidates in the field of medical image informatics, university teachers, doctors and other scientific research personnel. Interested in medical artificial intelligence.
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