Online Image Analysis Training in the UAE

This instructor-led, live training in the UAE (online or onsite) is aimed at beginner-level to intermediate-level researchers and laboratory professionals who wish to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.

By the end of this training, participants will be able to:

• Navigate the Fiji interface and utilize ImageJ’s core functions.
• Preprocess and enhance scientific images for better analysis.
• Analyze images quantitatively, including cell counting and area measurement.
• Automate repetitive tasks using macros and plugins.
• Customize workflows for specific image analysis needs in biological research.

Fiji is an open-source image processing package that integrates ImageJ (a program designed for scientific multidimensional images) along with numerous plugins for advanced scientific image analysis.

During this instructor-led live session, participants will learn how to utilize the Fiji distribution and its core ImageJ software to develop an application for image analysis.

By the end of the training, participants will be able to:

• Leverage Fiji's sophisticated programming capabilities and software modules to enhance ImageJ
• Combine large 3D images from overlapping segments
• Automatically update a Fiji installation upon startup using its built-in update system
• Select from a wide range of scripting languages to create custom image analysis solutions
• Utilize powerful libraries like ImgLib for extensive bioimage datasets with Fiji
• Deploy their application and collaborate with other researchers on similar projects

Course Format

• Interactive lecture and discussion.
• Absorbing exercises and ample practice opportunities.
• Practical implementation in a live-lab setting.

Customization Options for the Course

• To request tailored training for this course, please contact us to arrange.

Pattern Matching is a method employed to identify specific patterns within an image. It helps ascertain whether certain features are present in a captured image, such as identifying the expected label on a faulty product on an assembly line or verifying the precise dimensions of a part. This technique differs from "Pattern Recognition," which identifies general patterns based on extensive collections of related samples, by specifically defining what needs to be found and then indicating if the anticipated pattern is present.

Course Format

• This course covers the methodologies, technologies, and algorithms utilized in the realm of pattern matching as it pertains to Machine Vision.

Scilab is a robust, free, and open-source high-level programming language designed for handling scientific data. It is utilized in various fields such as statistics, graphics and animation, simulation, signal processing, physics, optimization, and more. The core data structure of Scilab is the matrix, which simplifies many types of problems compared to alternatives like FORTRAN and C derivatives. Additionally, it is compatible with languages such as C, Java, and Python, making it a valuable addition to existing systems.

In this instructor-led training session, participants will learn about the benefits of Scilab over alternatives like Matlab, understand the basics of Scilab syntax, explore some advanced functions, and interface with other commonly used programming languages based on demand. The course will culminate in a short project centered around image processing.

By the end of this training, participants will have a solid understanding of both basic and advanced functions of Scilab, along with resources to further expand their knowledge.

Audience

• Data scientists and engineers, particularly those interested in image processing and facial recognition

Format of the course

• The training will consist of lectures, discussions, exercises, intensive hands-on practice, and a final project.