Report on QBI 2018 Minisymposium on Digital Microscopy and Informatics

Written on Tue, Feb 6, 2018 8:44 PM by admin

The goal of the special session on digital microscopy and informatics is to showcase the applications of microscopy tools and techniques in biotech, pharma and life sciences industries. This year the session was focused on multiplexing techniques and the application of machine learning tools to microscopy image analysis. We had a total of 4 speakers. The session began with an overview talk  by Sripad Ram (Pfizer, Inc) who discussed the motivation for developing tissue based multiplexing approaches and presented the various multiplexing techniques that are currently being used for drug discovery and development. This was followed by a presentation from Shaban Muhammad (University of Warwick) on the application of machine learning techniques in the digital pathology space. He gave an overview of the work done in Prof. Nasir Rajpoot's group, where he is currently pursuing his PhD and presented results showing the application of traditional machine learning and deep learning methods for detecting malignancy from human tumor biopsies. The next speaker was Lars Pedersen (Visiopharm) who gave a demonstration on multiplexing image analysis using the Visiopharm software. The software provides a comprehensive suite of tools to analyze brightfield and fluorescence images and offers the capability to interact with other software packages such as R and Matlab. The final speaker of the session was France Rose (IBENS, France) who gave a presentation on quantifying spatial heterogeneity in cell responses to drug treatment. Her talk discussed an important question that arises in high content imaging which concerns with characterizing cells populations. She presented her ongoing research work that uses an unsupervised clustering method to group cells based on their morphological changes to drug treatment.The goal of the special session on digital microscopy and informatics is to showcase the applications of microscopy tools and techniques in biotech, pharma and life sciences industries. This year the session was focused on multiplexing techniques and the application of machine learning tools to microscopy image analysis. We had a total of 4 speakers. The session began with an overview talk  by Sripad Ram (Pfizer, Inc) who discussed the motivation for developing tissue based multiplexing approaches and presented the various multiplexing techniques that are currently being used for drug discovery and development. This was followed by a presentation from Shaban Muhammad (University of Warwick) on the application of machine learning techniques in the digital pathology space. He gave an overview of the work done in Prof. Nasir Rajpoot's group, where he is currently pursuing his PhD and presented results showing the application of traditional machine learning and deep learning methods for detecting malignancy from human tumor biopsies. The next speaker was Lars Pedersen (Visiopharm) who gave a demonstration on multiplexing image analysis using the Visiopharm software. The software provides a comprehensive suite of tools to analyze brightfield and fluorescence images and offers the capability to interact with other software packages such as R and Matlab. The final speaker of the session was France Rose (IBENS, France) who gave a presentation on quantifying spatial heterogeneity in cell responses to drug treatment. Her talk discussed an important question that arises in high content imaging which concerns with characterizing cells populations. She presented her ongoing research work that uses an unsupervised clustering method to group cells based on their morphological changes to drug treatment.