112,184 research outputs found
CMOS Vision Sensors: Embedding Computer Vision at Imaging Front-Ends
CMOS Image Sensors (CIS) are key for imaging technol-ogies. These chips are conceived for capturing opticalscenes focused on their surface, and for delivering elec-trical images, commonly in digital format. CISs may incor-porate intelligence; however, their smartness basicallyconcerns calibration, error correction and other similartasks. The term CVISs (CMOS VIsion Sensors) definesother class of sensor front-ends which are aimed at per-forming vision tasks right at the focal plane. They havebeen running under names such as computational imagesensors, vision sensors and silicon retinas, among others. CVIS and CISs are similar regarding physical imple-mentation. However, while inputs of both CIS and CVISare images captured by photo-sensors placed at thefocal-plane, CVISs primary outputs may not be imagesbut either image features or even decisions based on thespatial-temporal analysis of the scenes. We may hencestate that CVISs are more âintelligentâ than CISs as theyfocus on information instead of on raw data. Actually,CVIS architectures capable of extracting and interpretingthe information contained in images, and prompting reac-tion commands thereof, have been explored for years inacademia, and industrial applications are recently ramp-ing up.One of the challenges of CVISs architects is incorporat-ing computer vision concepts into the design flow. Theendeavor is ambitious because imaging and computervision communities are rather disjoint groups talking dif-ferent languages. The Cellular Nonlinear Network Univer-sal Machine (CNNUM) paradigm, proposed by Profs.Chua and Roska, defined an adequate framework forsuch conciliation as it is particularly well suited for hard-ware-software co-design [1]-[4]. This paper overviewsCVISs chips that were conceived and prototyped at IMSEVision Lab over the past twenty years. Some of them fitthe CNNUM paradigm while others are tangential to it. Allthem employ per-pixel mixed-signal processing circuitryto achieve sensor-processing concurrency in the quest offast operation with reduced energy budget.Junta de AndalucĂa TIC 2012-2338Ministerio de EconomĂa y Competitividad TEC 2015-66878-C3-1-R y TEC 2015-66878-C3-3-
Image informatics strategies for deciphering neuronal network connectivity
Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies
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The role of HG in the analysis of temporal iteration and interaural correlation
A proposal for a coordinated effort for the determination of brainwide neuroanatomical connectivity in model organisms at a mesoscopic scale
In this era of complete genomes, our knowledge of neuroanatomical circuitry
remains surprisingly sparse. Such knowledge is however critical both for basic
and clinical research into brain function. Here we advocate for a concerted
effort to fill this gap, through systematic, experimental mapping of neural
circuits at a mesoscopic scale of resolution suitable for comprehensive,
brain-wide coverage, using injections of tracers or viral vectors. We detail
the scientific and medical rationale and briefly review existing knowledge and
experimental techniques. We define a set of desiderata, including brain-wide
coverage; validated and extensible experimental techniques suitable for
standardization and automation; centralized, open access data repository;
compatibility with existing resources, and tractability with current
informatics technology. We discuss a hypothetical but tractable plan for mouse,
additional efforts for the macaque, and technique development for human. We
estimate that the mouse connectivity project could be completed within five
years with a comparatively modest budget.Comment: 41 page
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Optical coherence tomography measurements of biological fluid flows with picolitre spatial localization
This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.Interest in studying the human and animal microcirculation has burgeoned in recent years. In part
this has been driven by recent advances in volumetric microscopy modalities, which allow the study of the
3-D morphology of the microcirculation without the limitations of 2-D intra-vital microscopy. In this paper
we highlight the power of optical coherence tomography (OCT) to image the normal and pathological
microcirculation with picolitre voxel sizes. Both Doppler and speckle-variance methods are employed to
characterize complex rheological flows both in-vitro and in-vivo. GPU accelerated image registration
methods are demonstrated in order to mitigate problems of bulk tissue motion in methods based on speckle
decorrelation. In-vivo images of the human nailfold microcirculation are shown
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