About

Microscopes have long been essential for observing and analyzing biological structures at scales beyond human vision. Furthermore, the human eye is limited in its ability to extract precise quantitative information-such as length, area, and volume. Image analysis overcomes these limitations by enabling objective characterization, classification, and comparison of microscopic images using numerical parameters like feature size, shape, distribution, and clustering.

A typical microscope image processing workflow consists of three key steps: Image Acquisition - Capturing images through a microscope; Image Processing - Applying computational techniques to enhance and analyze the images and Quantitative Image Analysis - Extracting meaningful data, including area-based and cell-based measurements, as well as assessments of other tissue components. This approach has broad applications in biomedical research and diagnostics, including cancer staging and grading, automated cytology analysis, quantification of immunohistochemical markers, and investigations into disease mechanisms. In research settings, histologists and pathologists use image analysis to assess cellular and nuclear morphology, stromal composition, and tissue organization, among other critical factors.

Advancements in digital imaging and analysis have transformed histological studies. Tasks that once required hours of manual effort can now be completed in seconds with greater accuracy and reproducibility. Whole-slide imaging (WSI) technology enables the digitization of histological slides, allowing for seamless storage, sharing, and annotation. This digital transition not only facilitates remote collaboration and education but also enhances the precision of quantitative tissue analysis. The integration of digital microscopy, image processing, and artificial intelligence has revolutionized histopathology, paving the way for data-driven discoveries and large- scale statistical analysis. These innovations support global research collaborations and provide new opportunities for robust, reproducible insights into tissue-based studies.

Objective

• This workshop aims to systematically inspect, process, and analyze H&E-stained slides of human nervous tissue using Image J Fiji Software.
• Participants will gain hands-on experience in digital histological analysis, and learning techniques to extract and interpret quantitative data for research and clinical applications.

Coordinator

• Dr. Vasudha Kulkarni

Co-coordinators

• Dr. Vinay Kulkarni, Dr. Monalisa Mandal

Venue

• Sarvajna Mantapa Besides Ishaavasyam, Ground Floor, Manjushree Super-Speciality Building