Ultra-wide Field Of View
Ultra-wide Field Of View - Related Videos
07:20
Automated Behavioral Analysis of Large C. elegans Populations Using a Wide Field-of-view Tracking Platform
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Cited by 9 •
2018
We describe protocols for using the wide field-of-view nematode tracking platform (WF-NTP), which enables high-throughput phenotypic characterization of large populations of Caenorhabditis elegans. These protocols can be used to characterize subtle behavioral changes in mutant strains or in response to pharmacological treatment in a highly scalable fashion.
06:48
A Multimodal Wide-Field Fourier-Transform Raman Microscope
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2025
A wide-field Fourier-transform microscope, based on a compact and ultra-stable birefringent interferometer, allows the parallel acquisition of spectra for all pixels of a 2D detector. The time-domain approach enables the disentanglement of photoluminescence and Raman signals, and allows rapid Raman mapping (~5 ms/pixel) with ~1-µm spatial and 23-cm-1 spectral resolution.
07:35
Use of Ultra-high Field MRI in Small Rodent Models of Polycystic Kidney Disease for In Vivo Phenotyping and Drug Monitoring
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Cited by 14 •
2015
The use of ultra-high field MRI as a non-invasive way to obtain phenotypic information of rodent models for polycystic kidney disease and to monitor interventions is described. Compared with the traditional histological approach, MRI images can be acquired in vivo, allowing for longitudinal follow-up.
06:42
Wide-field Fluorescent Microscopy and Fluorescent Imaging Flow Cytometry on a Cell-phone
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Cited by 32 •
2013
We review our recent results on the integration of fluorescent microscopy and imaging flow cytometry tools on a cell-phone using compact and cost-effective opto-fluidic attachments. These cell-phone based micro-analysis devices might be useful for cytometric analysis, such as performing various cell counting tasks as well as for high-throughput screening of e.g., water samples in resource limited settings.
FAQs
Optical designs expand the observable angular or spatial field and direct the resulting light onto a detector capable of sufficient resolution. The detector matters because broad coverage alone does not ensure that cells, tissue structures, or organismal features remain distinguishable. Together, these elements retain both large-scale spatial relationships and biologically relevant local detail in the captured image.
Instead of building a larger representation from many separately positioned images, the approach captures more of the specimen or scene at once. This can reduce repeated repositioning and the need for image stitching, while making spatial context easier to preserve. The result is especially useful when relationships among cells, tissues, organisms, or behavioral features matter to interpretation.
Quantitative analysis turns broad image coverage into measurable biological information. It can help relate local features to larger anatomical, developmental, or ecological patterns rather than treating each feature in isolation. This connection allows researchers to examine how structures or behaviors are distributed across a specimen or environment and to use the preserved spatial context for systematic comparison.
A basic workflow positions the specimen or scene within the optical system, captures a broad image with sufficient detector resolution, and then applies quantitative image analysis to the recorded features. Because the system covers more area in one acquisition, researchers may spend less effort repositioning the sample or combining separate images before evaluating spatial relationships.
The capability can support surveys of cells, tissues, organisms, and behavioral environments. Its value changes with the biological scale: cellular or tissue imaging can retain local features within anatomical context, whereas organismal and behavioral imaging can show broader spatial arrangements. These applications make it useful for connecting observations across levels of biological organization.
Researchers can use the preserved spatial coverage to examine relationships between local features and broader anatomical, developmental, or ecological patterns. In behavioral environments, a larger captured scene can provide context for interpreting organismal activity. In specimens, the same approach helps place cellular or tissue-level observations within the surrounding structure, supporting more integrated biological interpretation.