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Lecture

Image Analysis Workflow: Batch Processing

In course

BIO-695: Image Processing for Life Science

Registration details will be announced via email. It takes place yearly from Sept./October to December & intends to teach image processing with a strong emphasis of applications in life sciences. The idea is to enable the participants to solve image-proces ...

Description

This lecture introduces the extraction of data from a segmentation workflow, focusing on regions of interest (ROIs) and the ROI manager. It emphasizes the importance of unbiased experiments with independent channels, covers the storage and use of results in Fiji, explains available measurements, and demonstrates how to create new measurements. The instructor also discusses performing image analysis for multiple images in batch.

In MOOC

Image Processing and Analysis for Life Scientists

Instructors (4)

Nicolas René Chiaruttini

Arne Seitz

04/1996-06/2000 Scientific co-worker at Philipps-University of Marburg, Dep. of Physical Chemistry 07/2000-10/2002 Post Doc at Max-Planck Unit for Structural Molecular Biology in Hamburg 11/2002-11/2005 Post Doc at European Molecular Biolohy Laboratory (EMBL), Cell Biology and Cell Biophysics Programme 11/2005-03/2009 Staff Scientist at Advanced Light Microscopy Facility, EMBL 04/2009- Head of Bioimaging and Optics platforme (BIOP), Ecole Polytechnique Fédérale de Lausanne (EPFL)

Romain Guiet

Olivier Burri

Official source

Related concepts (4)

Image analysis

Image analysis or imagery analysis is the extraction of meaningful information from s; mainly from s by means of techniques. Image analysis tasks can be as simple as reading bar coded tags or as sophisticated as identifying a person from their face. Computers are indispensable for the analysis of large amounts of data, for tasks that require complex computation, or for the extraction of quantitative information.

Medical image computing

Medical image computing (MIC) is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine. This field develops computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care. The main goal of MIC is to extract clinically relevant information or knowledge from medical images.

Image segmentation

In and computer vision, image segmentation is the process of partitioning a into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.

Digital image processing

Digital image processing is the use of a digital computer to process s through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over . It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems.

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Segmentation Techniques MOOC: Image Processing and Analysis for Life Scientists

Explores segmentation techniques in image analysis, including thresholding, clustering, region growing, and machine learning.

Analyze Particles MOOC: Image Processing and Analysis for Life Scientists

Covers the process of analyzing particles in images using Fiji software.

Results Tables: Managing and Saving Data MOOC: Image Processing and Analysis for Life Scientists

Covers setting measurements, managing results, using macro language functions, getting statistics, and saving results as CSV files.

Regions of Interest: Manipulation and Applications MOOC: Image Processing and Analysis for Life Scientists

Explores the significance of ROIs in measurements and how to manipulate them.

Introduction to ImageJ MOOC: Image Processing and Analysis for Life Scientists

Introduces ImageJ, covering installation, image display, macro recording, Fiji benefits, community, plugins, and scripting.

Related concepts (4)

Image analysis

Medical image computing

Image segmentation

Digital image processing