SLAS2016 Short Courses
Digital Image Processing and Analysis for the Laboratory Scientist: Theory and Application (Laptop Required)
This course takes a practical, hands-on approach to the application of digital image processing and analysis in a life-sciences laboratory. Diverse techniques and applications will be covered. Upon completion the attendee will be prepared to apply learned methodologies to their own experimental images to extract relevant information and summarize results.
This is a computer course. Charging stations will be available.
After registering for the course, participants should download and install the latest version of an open source image processing application called Fiji that matches the operating system that they will be using ().
Hardware & Software Requirements: All participants are required to provide their own laptop computer with Fiji and Java fully installed. Please choose the appropriate link under the "Fiji continuous release" heading. Fiji requires that Java be installed, version 6 or later. If the computer to be used does not have Java installed, it can be downloaded and installed from .
Who Should Attend:
Scientists and technologists...
- interested in obtaining a better understanding of image processing and analysis as it is applied to the life sciences,
- who use images to measure experimental outcomes,
- who want to improve the extraction of information from images collected in a laboratory setting,
- who need to automatically process large numbers of images, collect and summarize results
How You Will Benefit From This Course:
- Learn to use powerful, freely available image processing tools to analyze experimental images
- Gain a better understanding of image processing fundamentals and how image processing algorithms function
- Become skilled at authoring methods for extracting and measuring key features from images
- Automate the processing of large numbers of image files using scripting
- Summarize measurements, compute statistics and visualize results
- Image formats and file types
- Image processing and analysis functions, including thresholding, smoothing, sharpening, edge-detection, noise removal, segmentation, particle analysis, and feature extraction
- Applications in life sciences (cell-based assay, medical imaging, etc.)
- Scripting to automatically process large numbers of images
- Techniques for collecting and summarizing results
Matthew Fronheiser, Ph.D.
Matthew Fronheiser is a biomedical engineer with over 10 years experience in imaging technologies. He received a Ph.D. from Duke University for his research utilizing real-time 3D ultrasound to guide interventional devices. Upon graduation, Matthew performed research in photoacoustics, a hybrid imaging modality that can be used to generate oxygenation maps in tissue. His current position in the pharmaceutical industry involves the development of novel solutions for discovery research, including image analysis for cellular, histology, and medical imaging applications.
Mark F. Russo, Ph.D.
Mark Russo received a Ph.D. in Biochemical Engineering in 1989. He has held positions in the Biotechnology and Pharmaceutical industries in the fields of scientific computing, laboratory automation, data system design and development and software architecture. Mark has served the SLAS for many years, including as a short course instructor, session and track chair, and the Executive Editor of the Journal of Laboratory Automation (JALA). Mark has published extensively on topics related to scientific computing and laboratory automation, including scientific articles and book chapters. Currently, Mark works in the pharmaceutical industry where he architects software systems for drug discovery. Mark also teaches computer science at Rowan University in Glassboro, NJ.