2016
DOI: 10.4018/978-1-4666-8811-7.ch004
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iCellFusion

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… Show more

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Cited by 3 publications
(2 citation statements)
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“…Cell segmentation from the images was performed using the software 'iCellFusion' [32] and 'CellAging' [33], which perform automatic segmentation from phase contrast images (figure 1(A)) but allow manual corrections for increased accuracy. A 2D affine geometric transformation [34] was used to transform epifluorescence images (figure 1(B)) into the same resolution space as confocal images (figure 1(C)).…”
Section: Image Processing and Machine Learningmentioning
confidence: 99%
“…Cell segmentation from the images was performed using the software 'iCellFusion' [32] and 'CellAging' [33], which perform automatic segmentation from phase contrast images (figure 1(A)) but allow manual corrections for increased accuracy. A 2D affine geometric transformation [34] was used to transform epifluorescence images (figure 1(B)) into the same resolution space as confocal images (figure 1(C)).…”
Section: Image Processing and Machine Learningmentioning
confidence: 99%
“…Many available tools [7,8] were developed for bacterial colonies and are not well adapted for the analysis of fly images. They lack the flexibility of switching between a specialized automatic mode, which is essential for efficient processing, to manual intervention mode, which are often required to maximize the amount of samples acquired from each time-consuming experiment.…”
Section: Introductionmentioning
confidence: 99%