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文件名称：A review of content-based image retrieval in medical applications.pdf
文件大小：494KB
文件格式：PDF
更新时间：2020-06-29 20:29:11
图像处理算法 图像检索
ELSEVIER 出版集团. International Journal of Medical Informatics 上的经典论文。
Summary Content-based visual information retrieval (CBVIR) or content-based image
retrieval (CBIR) has been one on the most vivid research areas in the field of computer
vision over the last 10 years. The availability of large and steadily growing amounts of
visual and multimedia data, and the development of the Internet underline the need
to create thematic access methods that offer more than simple text-based queries or
requests based on matching exact database fields. Many programs and tools have been
developed to formulate and execute queries based on the visual or audio content and
to help browsing large multimedia repositories. Still, no general breakthrough has
been achieved with respect to large varied databases with documents of differing
sorts and with varying characteristics. Answers to many questions with respect to
speed, semantic descriptors or objective image interpretations are still unanswered.
In the medical field, images, and especially digital images, are produced in everincreasing quantities and used for diagnostics and therapy. The Radiology Department
of the University Hospital of Geneva alone produced more than 12,000 images a day. The cardiology is currently the second largest producer of digital images,
especially with videos of cardiac catheterization (∼1800 exams per year containing
almost 2000 images each). The total amount of cardiologic image data produced in the
Geneva University Hospital was around 1 TB . Endoscopic videos can equally produce enormous amounts of data