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iCellFusion: Tool for Fusion and Analysis of Live-Cell Images from Time-Lapse Multimodal Microscopy
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Author(s): João Santinha (UNINOVA – Instituto de Desenvolvimento de Novas Tecnologias, Portugal), Leonardo Martins (UNINOVA – Instituto de Desenvolvimento de Novas Tecnologias, Portugal), Antti Häkkinen (Tampere University of Technology, Finland), Jason Lloyd-Price (Tampere University of Technology, Finland), Samuel M. D. Oliveira (Tampere University of Technology, Finland), Abhishekh Gupta (Tampere University of Technology, Finland), Teppo Annila (Tampere University of Technology, Finland), Andre Mora (UNINOVA – Instituto de Desenvolvimento de Novas Tecnologias, Portugal), Andre S. Ribeiro (Tampere University of Technology, Finland)and Jose Ribeiro Fonseca (UNINOVA – Instituto de Desenvolvimento de Novas Tecnologias, Portugal)
Copyright: 2016
Pages: 29
Source title:
Biomedical Image Analysis and Mining Techniques for Improved Health Outcomes
Source Author(s)/Editor(s): Wahiba Ben Abdessalem Karâa (Taif University, Saudi Arabia & RIADI-GDL Laboratory, ENSI, Tunisia)and Nilanjan Dey (Department of Information Technology, Techno India College of Technology, Kolkata, India)
DOI: 10.4018/978-1-4666-8811-7.ch004
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Abstract
Temporal, multimodal microscopy imaging of live cells is becoming widely used in studies of cellular processes. In general, temporal sequences of images with functional and morphological data from live cells are acquired using multiple image sensors. The images from the different sources usually differ in resolution and have non-coincident fields of view, making the merging process complex. We present a new tool – iCellFusion – that performs data fusion of images from Phase-Contrast Microscopy and Fluorescence Microscopy in order to correlate the information on cell morphology, lineage and functionality. Prior to image fusion, iCellFusion performs automatic or computer-aided cell segmentation and establishes cell lineages. We exemplify its usage on time-lapse, multimodal microscopy images of bacteria producing fluorescent spots. We expect iCellFusion to assist research in Cell and Molecular Biology and the healthcare sector, where live-cell imaging is an increasingly important technique to detect and study diseases at the cellular level.
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