Lecture

Regions of Interest: Manipulation and Applications

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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 delves into the concept of Regions of Interest (ROIs) and their importance in accurate measurements. The instructor explains how to define ROIs to avoid background interference, compare signal localisation, and manipulate ROIs to distinguish between different cellular compartments. The lecture also introduces the XOR operator for ROI manipulation and suggests using CellProfiler for complex image analysis scenarios.

In MOOC

Image Processing and Analysis for Life Scientists

Nowadays, image-based methods are indispensable for life scientists. Light microscopy especially, has evolved from sketched out observations by eye, to high throughput multi-plane, multi-channel, multi-position and multimode acquisitions that easily produce thousands of information-rich images that must be quantified somehow to answer biological questions. This course will teach you core concepts from image acquisition to image filtering and segmentation, to help you tackle simple image analysis workflows

Instructors (4)

Olivier Burri

Expertise Development of bioimage analysis workflows and algorithms to extract quantitative data from microscopy imagesTools & Software: ImageJ/Fiji, CellProfiler, ilastik, Imaris, Arivis, Matlab, RStudio, IntelliJ, Eclipse, Jupyter NotebooksProgramming languages:Java, Groovy, JavaScript, TypeScript, PHP, Python, R, C, C , Matlab, Bash Expertise Development of bioimage analysis workflows and algorithms to extract quantitative data from microscopy imagesTools & Software: ImageJ/Fiji, CellProfiler, ilastik, I

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

Expertise Development of BioImage Analysis workflows and algorithms to extract quantitative data from microscopy images.BioSample Preparation : in vitro cell, organoid, time-lapse, fixation, staining strategies, actin, mitochondria, fluorescent protein expressionBioImage Acquisition : Widefield, Confocal, Whole Slide Imaging, Super-resolution (SIM, STORM, STED), FRET, FRAP, FLIMBioImage Analysis: Colocalisation analysis, Deconvolution, Time-lapse , Whole Slide ImagingTools & Software: ImageJ/Fiji, QuPath, i

Nicolas René Chiaruttini

Official source

Related concepts (8)

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.

Cell (biology)

The cell is the basic structural and functional unit of all forms of life. Every cell consists of cytoplasm enclosed within a membrane, and contains many macromolecules such as proteins, DNA and RNA, as well as many small molecules of nutrients and metabolites. The term comes from the Latin word cellula meaning 'small room'. Cells can acquire specified function and carry out various tasks within the cell such as replication, DNA repair, protein synthesis, and motility. Cells are capable of specialization and mobility within the cell.

Cell biology

Cell biology (also cellular biology or cytology) is a branch of biology that studies the structure, function, and behavior of cells. All living organisms are made of cells. A cell is the basic unit of life that is responsible for the living and functioning of organisms. Cell biology is the study of the structural and functional units of cells. Cell biology encompasses both prokaryotic and eukaryotic cells and has many subtopics which may include the study of cell metabolism, cell communication, cell cycle, biochemistry, and cell composition.

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