Extracting Patterns of Lymphocyte Fluorescence from Digital Microscope Images

نویسندگان

  • Tim W. Nattkemper
  • Helge Ritter
  • Walter Schubert
چکیده

A system for full-automatic extraction of uorescence information from lymphocytes in digital microscope images is presented. It is applied on samples of lymphocytes invading muscle tissue. From a single sample images are taken using n di erent uorochrome antibody markers. In every image a di erent subset of the lymphocytes appears through uorescence. The uorescent cells in every image are detected by an arti cial neural network. After detection, corresponding uorescences of each cell in di erent images are collected in lists of length n, called marker combination patterns. Each binary element of a pattern represents, if a cell was uorescent (1), or not (0) in a particular image. The whole algorithm of detection and correspondence analysis is easy to adapt and computes fast. This automation allows us to gain reproducible data and opens the door for a statistical analysis of a large number of uorescence

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multiresolution Multiscale Active Mask Segmentation of Fluorescence Microscope Images.

We propose an active mask segmentation framework that combines the advantages of statistical modeling, smoothing, speed and flexibility offered by the traditional methods of region-growing, multiscale, multiresolution and active contours respectively. At the crux of this framework is a paradigm shift from evolving contours in the continuous domain to evolving multiple masks in the discrete doma...

متن کامل

Extracting information from text and images for location proteomics

There is extensive interest in automating the collection, organization and summarization of biological data. Data in the form of figures and accompanying captions in literature present special challenges for such efforts. Based on our previously developed search engines to find fluorescence microscope images depicting protein subcellular patterns, we introduced text mining and Optical Character...

متن کامل

Location proteomics - Building subcellular location trees from high resolution 3D fluorescence microscope images of randomly-tagged proteins

The overall object of proteomics is to characterize all of the proteins expressed in a given cell type. With the rapid development of random gene tagging technology and high resolution fluorescence microscopy, it has become possible to generate libraries of digital images depicting the location patterns of most proteins in any given cell type. While the subcellular location of a protein is impo...

متن کامل

Location proteomics: systematic determination of protein subcellular location.

Proteomics seeks the systematic and comprehensive understanding of all aspects of proteins, and location proteomics is the relatively new subfield of proteomics concerned with the location of proteins within cells. This review provides a guide to the widening selection of methods for studying location proteomics and integrating the results into systems biology. Automated and objective methods f...

متن کامل

Searching Online Journals for Fluorescence Microscope Images Depicting Protein Subcellular Location Patterns

There is extensive interest in automating the collection, organization and analysis of biological data. Data in the form of images present special challenges for such efforts. Since fluorescence microscope images are a primary source of information about the location of proteins within cells, we have set as a long-term goal the building of a knowledge base system that can interpret such images ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1999