Farsight Courses OneWeek

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= Methodology =
 
= Methodology =

Revision as of 14:44, 18 September 2009

Contents

Audience

  • Researchers in academic & industrial laboratories who make active use of optical microscopes, and desire to make image-based quantitative measurements for hypothesis testing, screening, and modeling
  • Particular emphasis is placed on fluorescence based multi-dimensional microscopy (3-D confocal/multi-photon, time-lapse, multi-channel, etc.)
  • This course will provide instruction on biological image analysis concepts/theory, and hands-on practical learning.

Learning Objectives

  • Upon successful completion of this course, the participants will have a working knowledge of basic open-source computational image analysis tools (FARSIGHT, ITK, VTK, Paraview, Overview) to generate quantitative measurements from 3D/4D/5D microscopy image data.
  • Developing skills on the use of a selected subset of computational methods from the ITK and FARSight libraries.
  • Developing awareness of more advanced tools that are part of the ITK and FARSight libraries, as well as the support resources available such as email forums and Wiki pages.
  • Specifically,
    • Ability to read, visualize and write images files for various common formats.
    • Ability to design computational scripts for image pre-processing to correct for common imaging artifacts (noise, blur, spectral overlap).
    • Being able to segment common types of biological objects (cell, nuclei, membranes, micro-vasculature, neurites, foci) in 2D and 3D images of cells and tissue.
    • Being able to perform edit-based validation of segmentation results.
    • Being able to perform registration and montaging.
    • Being able to perform cell and organelle tracking, and analysis of changes in time-lapse image series.
    • Being able to compute morphological measurements of biological objects.
    • Being able to compute associative measurements linking two or more biological objects.
    • Being able to summarize and conduct statistical analysis of measurements.

Pre-requisites

  • Familiarity with contemporary computers PC/Mac/Linux
  • Basic knowledge of programming using scripting languages
    • We will use Python
  • Familiarity with common viewing tools and file formats

Content

Day 1

Morning

  • 8:00am-9:00am Introduction and Overview (B.R.)
  • 9:00am-10:00am Programming environment and data visualization (L.I.)
  • 10:00am-10:30am Break
  • 10:30am-12:00pm Hands-on session 1
    • Reading / Writing images from different file formats (C.R.)
    • Visualization methods
  • 12:00pm-1:00pm Working Lunch

Afternoon

  • 1:00pm-1:20pm More Python basics (L.I.)
  • 1:20pm-2:00pm Hands-on exercises on pre-processing, segmentation and visualization using Python-wrapped ITK (L.I.)
  • 2:00pm-2:30pm Break
  • 2:30pm-3:10pm Fundamental of image processing (B.R.)
  • 3:15pm-5:00pm Hands-on session
    • Pixel level image processing
      • Grayscale morphology
      • Image smoothing, denoising
      • Deconvolution (C.P).

Day 2

Morning

  • 10:00am-10:30am Break


  • 12:00pm-1:00pm Working Lunch


Afternoon

  • 2:00pm-2:30pm Break

Day 3

Morning

  • 10:00am-10:30am Break


  • 12:00pm-1:00pm Working Lunch


Afternoon

  • 2:00pm-2:30pm Break

Day 4

Morning

  • 10:00am-10:30am Break


  • 12:00pm-1:00pm Working Lunch


Afternoon

  • 2:00pm-2:30pm Break

Day 5

Morning

  • 10:00am-10:30am Break


  • 12:00pm-1:00pm Working Lunch


Afternoon

  • 2:00pm-2:30pm Break

Methodology

Personal tools