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Since the 1990s, hybrid imaging by means of software and hardware image fusion alike allows the intrinsic combination of functional and anatomical image information.
Magnetic Resonance Imaging (MRI) data collection is influenced by SNR, hardware, image time, and other factors.
[via Hot Hardware; image credit: John Berry / The Post-Standard].
The system uses a four degree of freedom (4 DOF) pan-tilt-verge stereo camera head (built in-house) coupled with an inexpensive hardware image processor.
Along the way, several critical incidents occurred, in the form of technical setbacks to do with camera hardware, image processing and the software from an external supplier.
In a pilot study with 109 candidates, we confirmed the qualifications of trained personnel, and tested the image acquisition hardware, image analysis software, digital data transmission, and storage and retrieval systems for BCDRT [ 15].
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Qualitatively, the hardware images look very similar, with the hardware images perhaps slightly darker near the point source target.
Over the past 5 years, significant technological breakthroughs in imaging hardware and image processing algorithms have also been introduced, enabling specific radiotracer imaging for improved characterization of targeted cellular and functional processes in clinical routine.
Compared with imaging hardware development, image processing has often been the bottleneck for maximizing the use of the direct sensing information, e.g. current image segmentation methods are still restricted to relatively low-solid concentrations, therefore research is needed to develop methods for handling high-solid concentrations.
Image Quality Assessment (IQA) plays an important role in assessing any new hardware, software, image acquisition techniques, image reconstruction or post-processing algorithms, etc.
By using the bridge hardware, the image processor can easily initialize any DVP-compatible image sensor and capture image frames.
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