Image analysis in cytology: DNA-histogramming versus cervical smear prescreening.
The visual inspection of cellular specimens and histological sections through a light microscope plays an important role in clinical medicine and biomedical research. The human visual system is very good at the recognition of various patterns but less efficient at quantitative assessment of these patterns. Some samples are prepared in great numbers, most notably the screening for cervical cancer, the so-called PAP-smears, which results in hundreds of millions of samples each year, creating a tedious mass inspection task. Numerous attempts have been made over the last 40 years to create systems that solve these two tasks, the quantitative supplement to the human visual system and the automation of mass screening. The most difficult task, the total automation, has received the greatest attention with many large scale projects over the decades. In spite of all these efforts, still no generally accepted automated prescreening device exists on the market. The main reason for this failure is the great pattern recognition capabilities needed to distinguish between cancer cells and all other kinds of objects found in the specimens: cellular clusters, debris, degenerate cells, etc. Improved algorithms, the ever-increasing processing power of computers and progress in biochemical specimen preparation techniques make it likely that eventually useful automated prescreening systems will become available. Meanwhile, much less effort has been put into the development of interactive cell image analysis systems. Still, some such systems have been developed and put into use at thousands of laboratories worldwide. In these the human pattern recognition capability is used to select the fields and objects that are to be analysed while the computational power of the computer is used for the quantitative analysis of cellular DNA content or other relevant markers. Numerous studies have shown that the quantitative information about the distribution of cellular DNA content is of prognostic significance in many types of cancer. Several laboratories are therefore putting these techniques into routine clinical use. The more advanced systems can also study many other markers and cellular features, some known to be of clinical interest, others useful in research. The advances in computer technology are making these systems more generally available through decreasing cost, increasing computational power and improved user interfaces. We have been involved in research and development of both automated and interactive cell analysis systems during the last 20 years. Here some experiences and conclusions from this work will be presented as well as some predictions about what can be expected in the near future.
- 원문이 없습니다.
- 원문이 없습니다.
유료 다운로드의 경우 해당 사이트의 정책에 따라 신규 회원가입, 로그인, 유료 구매 등이 필요할 수 있습니다. 해당 사이트에서 발생하는 귀하의 모든 정보활동은 NDSL의 서비스 정책과 무관합니다.
원문복사신청을 하시면, 일부 해외 인쇄학술지의 경우 외국학술지지원센터(FRIC)에서
무료 원문복사 서비스를 제공합니다.
NDSL에서는 해당 원문을 복사서비스하고 있습니다. 위의 원문복사신청 또는 장바구니 담기를 통하여 원문복사서비스 이용이 가능합니다.
- 이 논문과 함께 출판된 논문 + 더보기