![]() Particularly, CLSMs excel at collecting stacks of optical slices from hundreds of microns thick specimens to generate three-dimensional (3D) images, as well as (4D) time series of living cells and tissues. ĭeconvolution-based Widefield as well as CLSM systems routinely generate crisp three-dimensional multichannel time-series data of fluorescence labelled targets in cells. High-resolution digital images with many dimensions can be generated almost indefinitely by contemporary scanners. Automatic, fast, and reliable collection of larger datasets and hardware module-based image analysis during acquisition are now standards. Recent major advances in computer hardware modules (particularly in graphics processors) have increased the imaging throughput in microscopy. Several 2D visualization software programs, compatible with typical personal computers, have been developed and made publicly available to aid researchers and pathologists over the previous two decades. Historically, scientists used simple or compound microscopes to inspect and sketch the structure of cellular organisms however, with later advances in computing power and the development of modern microscopes, it became possible to automatically capture the structure of cellular organisms in a digital format and save it in two-dimensional (2D) digital data files. The samples are studied by researchers to better understand how cellular organisms operate. Much of our understanding of the cellular world is based on the study of microscopy images. NO -: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the paper.įunding: This work was supported by the Marie Sklodowska Curie ITN-EID, Horizon 2020 project IMAGE-IN (grant agreement No 861122). Received: SeptemAccepted: DecemPublished: December 30, 2022Ĭopyright: © 2022 Gupta et al. Bastião Silva L, Heintzmann R (2022) IMAGE-IN: Interactive web-based multidimensional 3D visualizer for multi-modal microscopy images. We evaluate the performance by comparing the loading and rendering timings of a heterogeneous dataset of multichannel CLSM and FIB-SEM images on two devices with installed graphic cards, as well as comparing rendered image quality between ClearVolume (the ImageJ open-source desktop viewer), Napari (the Python desktop viewer), Imaris (the closed-source desktop viewer), and our proposed IMAGE-IN web viewer.Ĭitation: Gupta Y, Costa C, Pinho E, A. The software accepts a sequence of image files or stacked 3D images as input and offers a variety of viewing options ranging from 3D volume/surface rendering to multiplanar reconstruction approaches. This new visualization platform includes intuitive multidimensional opacity fine-tuning, shading on/off, multiple blending modes for volume viewers, and the ability to handle multichannel volumetric data in volume and surface views. Here we present IMAGE-IN, an interactive web-based multidimensional (N-D) viewer designed specifically for confocal laser scanning microscopy (CLSM) and focused ion beam scanning electron microscopy (FIB-SEM) data, with the goal of assisting biologists in their visualization and analysis tasks and promoting digital workflows. ![]() Since “seeing is believing”, it is important to have easy access to user-friendly visualization software. The multiple dimensions are commonly associated with space, time, and color channels. Advances in microscopy hardware and storage capabilities lead to increasingly larger multidimensional datasets.
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