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Nikon Instruments has announced a powerful image analysis and processing module for NIS-Elements that leverages Deep learning and Artifical Intelligence. NIS.ai is a suite of new AI-based processing tools that utilises convolutional neural networks to learn from small training datasets supplied by the user. The training results can then be easily applied to process and analyse huge volumes of data, enabling researchers to increase throughput and expand their application limits.

NIS.ai includes a suite of applications for predictive imaging, image segmentation and processing:

Convert.ai: Convert.ai learns related patterns present in two different imaging channels. After training, Convert.ai can then predict the pattern in the second channel even when presented with only the first channel. DAPI-based staining of nuclei is a common method for cell segmentation and counting. Convert.ai can be trained to predict where the DAPI label would be based on unstained DIC or phase-contrast images. This enables users to perform nuclei-based image analysis without ever having to stain samples with DAPI or acquire a fluorescent channel.

Segment.ai: Segment.ai enables complex structures to be easily identified and segmented. Neurites in phase-contrast images are traditionally difficult to define by classic thresholding. Segment.ai can be trained on a small subset of hand-traced neurites to automatically detect and segment neurites from thousands of untraced datasets.

Enhance.ai: Imaging dim fluorescent samples or applications that require low-level light exposure typically result in compromised image quality with poor signal-to-noise ratio. Enhance.ai learns what a high signal-to-noise image looks like by comparing under-exposed and optimally-exposed images. Enhance.ai can then restore details in under-exposed or dim fluorescent images, enabling researchers to gain more insights from their low-signal imaging applications.

Denoise.ai: Launched earlier this year, Denoise.ai removes shot noise from resonant confocal images and can be performed in real-time. Applying Denoise.ai to resonant confocal imaging enables users to acquire confocal images at ultra high speed without sacrificing image quality.

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If you work with multiphoton microscopy, three-photon imaging allows you to image even deeper into tissues with improved contrast.

Semrock's new 3-photon short-pass dichroic beamsplitter allows super-resolution flatness imaging of green and red genetically expressed fluorescence in a standard epi-fluorescence microscope configuration. This dichroic beamsplitter is optimised to reflect 1300nm and 1700nm laser pulses with minimal temporal pulse broadening. With industry-leading flatness, this dichroic beamsplitter allows minimal focus shift and optical wavefront aberrations of the laser beam spot to enable your preferred imaging technique.

For further information please contact us or read more.

WPI has released a line of premium stereotaxic instruments designed for research. These frames and accessories stand up to daily laboratory use and offer the precision you demand. They are committed to bringing you the quality products you need, and the affordable solutions you want.

A broad variety of stereotaxic instruments are available for various applications.

• Basic frames with single or dual arms
• Motorised and digital frames
• Parallel rail frames

WPI stereotaxic frames

• Are convenient to use and highly accurate (to 100µm)
• Offer smooth and versatile movement
• Provide stability and adaptability

For further information please contact us or read more.

Perfusion, media exchange, drug delivery and mxing can be easily programmed without disturbing your sample using the new PMD-D35 Perfusion/Media Exchange System from Tokai Hit.

It enables uniform mixing of the media and drug offering stress-free, safe and highly repeatable experiments by keeping the media level even. It is suitable for long-term single cell imaging and prevents media evaporation and contamination.

For further information please contact us or read more.

The development of heterogeneous materials like polymer composites, blends and multilayers are of considerable importance in the chemicals industry. Bulk viscoelastic measurements are routine in establishing structure-property relationship for these materials. However, materials R&D often produces composites that contain nano-sized portions that do not exist in the bulk or that have properties influenced by the proximity of other components. A quantitative means of measuring the viscoelastic properties of such mterials at the nanoscale has been a long-standing and elusive goal for atomic force microscopy (AFM). While AFM has the sensitivity and resolution needed to do the measurement, traditional AFM-based approaches are hampered by difficult calibration, poorly defined measurement frequency, and inadequate modeling of the tip-sample interation.

Now, with the development of the AFM-nDMA mode from Bruker, these pitfalls can be avoided and the frequency and temperature depedence of viscoelastic properties in rheologically relevant ranges can be directly measured with 10nm spatial resolution. Read more or download the application note.