Tag Archives: Image analysis

Lecture notes : Algortihms used for Medical Image Processing

This course has two components. On the one hand, it is an introduction to digital image analysis presenting selected fundamental problems in medical image analysis, computer vision, photo/video editing, and graphics. We cover such basic concepts as image segmentation, registration, object recognition/matching, tracking, texture, etc. On the other hand, this is an applied course on standard computer science algorithms where students develop practical understanding of dynamic programming, graph based algorithms, computational geometry methods, etc. In fact, image analysis provides a stimulating environment for studying algorithms as their outputs can be intuitively visualized. Students with previous background in algorithms will be exposed to applications in image analysis, while students already familiar with problems in imaging will learn efficient methods based on standard CS algorithms. The course emphasizes the design, analysis, and implementation of algorithms in the context of 2D/3D medical images, photo and video data.

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IEEE Workshop on Mathematical Methods in Biomedical Image Analysis 2012

Call for papers
Biomedical image analysis is a fast evolving field driven by the advancement of imaging modalities and high content screening techniques. Many clinical applications are also emerging that use biomedical image processing for decision support.  The workshop will bring together researchers in computer vision, medical imaging, computational biology, graphics and robotics communities interested in problems that involve mathematical modeling or analysis in biomedical images, which include emerging molecular and cellular images. 
Topics of interests include but are not limited to:
  •     2D/3D/4D Registration
  •     Biomedical Image Databases / Retrieval
  •     Biomedical Image Motion Analysis
  •     Biomedical Image Reconstruction Methods
This is a preview of IEEE Workshop on Mathematical Methods in Biomedical Image Analysis 2012. Read the full post (487 words, 1 image, estimated 1:57 mins reading time)