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Bioimagexd: an Open, General-Purpose and High-Throughput Image-Processing Platform FOCUS ON BIOIMAGE INFORMATICS PERSPECTIVE BioImageXD: an open, general-purpose and high-throughput image-processing platform Pasi Kankaanpää1, Lassi Paavolainen2, Silja Tiitta1, Mikko Karjalainen2, Joacim Päivärinne1, Jonna Nieminen1, Varpu Marjomäki2, Jyrki Heino1 & Daniel J White2,3 BioImageXD puts open-source computer science BioImageXD in practice with user-friendly, auto- tools for three-dimensional visualization and mated, multiparametric image analyses of the move- analysis into the hands of all researchers, through a ment, clustering and internalization of integrins. user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses Criteria in BioImageXD development or undisclosed algorithms and enables publication Open. Our goal was to develop software that is trans- of precise, reproducible and modifiable workflows. parent, with open and documented source code and It allows simple construction of processing pipelines no undisclosed algorithms or hidden processing the and should enable biologists to perform challenging user is unaware of or cannot control. It is our view that analyses of complex processes. We demonstrate its software for scientific data analysis, in contrast to engi- performance in a study of integrin clustering in neering, is best when it is not a ‘black box’. Different response to selected inhibitors. implementations of the same method can often give dif- Bioimaging has emerged as one of the key tools in bio- ferent results, the reasons for which only become clear medical research. New imaging devices are appearing by comparing the source codes. Increasingly (and cor- rapidly, producing large multidimensional images with rectly in our view), disclosure of source code for image- several data channels in medium-to-high throughput. processing methods and algorithms is recommended in Specialized software is required to extract interpreta- scientific research4–6. Publication of scientific software ble results from such data. Despite recent and ongoing tools also often requires the source code (the method) © 2012 Nature America, Inc. All rights reserved. America, Inc. © 2012 Nature progress in both commercial and academic software, to be open, as is the norm for all other protocols in availability of user-friendly tools often remains a limit- sample preparation, experimental procedure and data ing factor, especially in complex and high-throughput analysis. BioImageXD (Fig. 1) is released under a GNU npg applications1–3. We formed a multidisciplinary General Public License version 2 (http://www.gnu.org/ consortium to develop bioimage processing soft- licenses/gpl-2.0.html); the source code is fully open. ware (Supplementary Methods) that is (i) open: Subsampling of image data in software may occur has open-source code; (ii) extensive: has many fea- without the user’s knowledge, for instance in the inter- tures; (iii) usable: is inexpensive, easy to use and fast; est of user-interface responsiveness, and may affect (iv) adjustable: all features are adjustable and combin- data interpretations. Although BioImageXD can also able into pipelines; (v) applicable: especially for vali- subsample image data, subsampling is never done dated batch processing of multidimensional time-lapse automatically and is always clearly indicated. All pro- data; and (vi) extendable: with a modular design that cessed image data are written into new files by user allows addition of new functionality. action, with processing information automatically We now report the release of version 1.0 of saved, making workflows retraceable and minimiz- BioImageXD (http://www.bioimagexd.net/). We ing inadvertent processing. A concise user guide is explain for each of our design criteria why we consider provided with the software. them important and describe how BioImageXD fulfills them. We then compare BioImageXD to other Extensive. We sought to develop software with a software. Finally we demonstrate the capabilities of comprehensive collection of features for processing, 1Department of Biochemistry and Food Chemistry, University of Turku, Turku, Finland. 2Department of Biological and Environmental Science, and Nanoscience Center, University of Jyväskylä, Jyväskylä, Finland. 3Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. Correspondence should be addressed to P.K. ([email protected]). PUBLISHED ONLINE 28 JUNE 2012; DOI:10.1038/NMETH.2047 nature METHODS | VOL.9 NO.7 | JULY 2012 | 683 PERSPECTIVE FOCUS ON BIOIMAGE INFORMATICS Figure 1 | BioImageXD GUI. Screenshot shows toolbars and menus (top), a file tree of the loaded images (left), and the currently active visualization (middle), showing here a two- channel merged image with a user-defined region of interest. On the right are settings for the currently active task, showing here the graphical intensity transfer function, a central feature in accurate image adjustment. visualization and analysis. Bioimaging applications today are greatly varied, and a single software package should be able to meet as many needs as possible, without requiring extra programming. BioImageXD has been designed to be a general-purpose processing program, featuring approxi- mately 220 tools (Supplementary Table 1). Processing tools include deconvolution, registration, 32 tools for basic mathematical and logical process- BioImageXD (Fig. 1), enabling the user to check this graph and ing, and six noise-reduction algorithms. Visualization tools evaluate possible data loss (which happens in principle every time include an interactive three-dimensional (3D) mode with 11 brightness or contrast, for example, is increased). simultaneously visible modules for creating volume render- Studies of colocalization (whether two markers occupy the same ings, surface renderings, 3D measurements and so on (Fig. 2, spatiotemporal location) are very common but are often poorly Supplementary Fig. 1 and Supplementary Video 1). Movies executed in part owing to tool inaccessibility7,8. In BioImageXD, can be created with an animator supporting two different com- colocalization can be visualized with maps and histograms, and binable techniques: keyframes and virtual camera flight paths quantified with 54 parameters. Three statistical significance (Supplementary Fig. 2 and Supplementary Videos 2 and 3). methods9–11, automatic threshold determination9, and both Analysis tools feature both voxel-based and object-based object-based and pixel-based colocalization are supported. approaches. For the latter, 17 methods are available for seg- menting image data into quantifiable objects (Supplementary Usable. Our aim was to make BioImageXD inexpensive and simple Fig. 3 and Supplementary Video 4) based on thresholding, to install and run on any common computer. One of the bottlenecks watershed, region growing and active contours. A 3D motion of bioimage processing is that the required software often comes tracking algorithm can follow the movement of different fea- with an expensive and restrictive license policy, limiting availabil- © 2012 Nature America, Inc. All rights reserved. America, Inc. © 2012 Nature tures, such as a few cells, or hundreds of segmented objects in ity to isolated workstations that may also control microscopes. a cell (Supplementary Video 5). BioImageXD can be used free of charge on any computer with Many scientific journals have guidelines for setting up the either 32-bit or 64-bit Windows (XP, Vista or 7), Mac OSX (10.6 npg intensity-transfer function (used to adjust, for instance, bright- or 10.7) or modern Linux operating systems. The software consists ness and contrast)5. The function is represented graphically in of a single package that is simple to install. Most features work without specific system requirements, but a b c if processor-intensive tasks progress slowly, 24.72 µm BioImageXD can subsample images on loading 4.64 µm Figure 2 | Examples of visualizations created with 108° BioImageXD. (a) Gallery mode for viewing 3D images as 2D slices. Scale bar, 10 µm. (b) Volume rendering of 2D slices into a 3D image, shown here d e with a cutting plane. (c) Surface rendering, shown here with 3D distance and angle measurements. (d) Several semitransparent surfaces created at the same time. (e) Volume rendering (blue actin z filaments) and surface rendering (red integrins) x y displayed together, shown here with a 3D axis marker. (f) Volume rendered cell-surface proteins. f g h i (g) A 3D visualization of molecular models; detail of an integrin I-domain model37. (h) Warp z scalar rendering of a cell showing atomic force microscopy data in three dimensions. (i) The 3D renderings can be animated in various ways, such y x as by specifying a ‘flight path’ (red line) for a virtual camera. 684 | VOL.9 NO.7 | JULY 2012 | nature METHODS FOCUS ON BIOIMAGE INFORMATICS PERSPECTIVE (this is clearly indicated and easily undone). Data sets larger than Extendable. As scientific research continuously spawns new the computer’s RAM can be visualized and processed. questions, requiring implementation of new or modified tools to Bioimaging software should be easy and efficient to use, answer them, bioimaging software should build upon and engi- with an intuitive graphical user interface (GUI)12. The GUI of neer compatibility with existing libraries and tools17. We therefore BioImageXD is based on a single large window (Fig. 1) with an designed BioImageXD to have modular, extendable software archi- unchanged layout. Advanced settings are always available but are tecture,
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