Open source bioimage informatics for cell biology

Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery

Non-line-of-sight imaging using a time-gated single photon avalanche diode

By using time-of-flight information encoded in multiply scattered light, it is possible to reconstruct images of objects hidden from the camera’s direct line of sight. Here, we present a non-line-of-sight imaging system that uses a single-pixel, single-photon avalanche diode (SPAD) to collect time-of-flight information. Compared to earlier systems, this modification provides significant improvements in terms of power requirements, form factor, cost, and reconstruction time, while maintaining a comparable time resolution. The potential for further size and cost reduction of this technology make this system a good base for developing a practical system that can be used in real world applications

ImageJ2: ImageJ for the next generation of scientific image data

ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science. Due to these new and emerging challenges in scientific imaging, ImageJ is at a critical development crossroads. We present ImageJ2, a total redesign of ImageJ offering a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. ImageJ2 provides a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs

Validation of an arterial constitutive model accounting for collagen content and crosslinking

During the progression of pulmonary hypertension (PH), proximal pulmonary arteries (PAs) increase in both thickness and stiffness. Collagen, a component of the extracellular matrix, is mainly responsible for these changes via increased collagen fiber amount (or content) and crosslinking. We sought to differentiate the effects of collagen content and cross-linking on mouse PA mechanical changes using a constitutive model with parameters derived from experiments in which collagen content and cross-linking were decoupled during hypoxic pulmonary hypertension (HPH). We employed an eight-chain orthotropic element model to characterize collagen’s mechanical behavior and an isotropic neo-Hookean form to represent elastin. Our results showed a strong correlation between the material parameter related to collagen content and measured collagen content (R2 = 0.82, P < 0.0001) and a moderate correlation between the material parameter related to collagen crosslinking and measured crosslinking (R2 = 0.24, P = 0.06). There was no significant change in either the material parameter related to elastin or the measured elastin content from histology. The model-predicted pressure at which collagen begins to engage was ∼25 mmHg, which is consistent with experimental observations. We conclude that this model may allow us to predict changes in the arterial extracellular matrix from measured mechanical behavior in PH patients, which may provide insight into prognoses and the effects of therapy

OpenSPIM - an open access platform for light sheet microscopy

Light sheet microscopy promises to revolutionize developmental biology by enabling live in toto imaging of entire embryos with minimal phototoxicity. We present detailed instructions for building a compact and customizable Selective Plane Illumination Microscopy (SPIM) system. The integrated OpenSPIM hardware and software platform is shared with the scientific community through a public website, thereby making light sheet microscopy accessible for widespread use and optimization to various applications.Comment: 7 pages, 3 figures, 6 supplementary videos, submitted to Nature Methods, associated public website http://openspim.or

Meeting in the Middle: Towards Successful Multidisciplinary Bioimage Analysis Collaboration

With an increase in subject knowledge expertise required to solve specific biological questions, experts from different fields need to collaborate to address increasingly complex issues. To successfully collaborate, everyone involved in the collaboration must take steps to "meet in the middle". We thus present a guide on truly cross-disciplinary work using bioimage analysis as a showcase, where it is required that the expertise of biologists, microscopists, data analysts, clinicians, engineers, and physicists meet. We discuss considerations and best practices from the perspective of both users and technology developers, while offering suggestions for working together productively and how this can be supported by institutes and funders. Although this guide uses bioimage analysis as an example, the guiding principles of these perspectives are widely applicable to other cross-disciplinary work