Course - Woods Hole, MA, United States
Recent advances in fluorescence microscopy have enabled unprecedented progress in cellular and developmental biology.
Imaging has become a component of nearly every cell-biological investigation at all scales, from single molecules to whole tissues, and research modalities, from reconstitution experiments to genome-wide screening;
However, these fast-paced developments in imaging technology have remained unmatched by developments in image analysis software. Most of the published image data in biology are still processed by hand and interpreted by qualitative visual inspection.
Currently, there are very few curricula, in universities and national laboratories, dedicated to the mathematical, statistical, software, and machine learning methods required to transform raw microscopy image data into rigorous biological knowledge. This course is targeted to fill this void by training a next generation of life scientists in the mathematical foundation and implementation of algorithms for image analysis.
Topics covered in this course include: image enhancement, segmentation, tracking, feature extraction, image classification, machine learning, noise analysis and uncertainty prediction, and statistical hypothesis testing. All topics will be covered in theory lectures and computer exercises. Exercises will be done on images from ongoing research projects in the instructors’ labs and will target actual research questions. An important subject in the course will be software design, addressing both the implementation of optimized algorithms and sharable code, including programming in teams.
Organization: Marine Biological Laboratory
Sun, Oct 13, 2013 - Wed, Oct 23, 2013 (9:00 am - 5:00 pm)
Marine Biological Laboratory, Woods Hole, United States
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