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MedTech Outlook | Saturday, November 16, 2019
Research analysts from the University of Strathclyde recently developed a miniaturized pipe organ, inspired by the pipes observed in the full-sized instrument. Through this development, enhanced image quality can be achieved from ultrasound scanners by expanding the frequency range of the emitted sound waves.
Tony Mulholland, professor and head of the mathematical department, University of Strathclyde, stated that there are varieties of designs available in the musical instruments, but the common entity amongst them is the variation in sound, observed from the broad range of frequencies. So, with this insight about different frequencies of sound, numerous design ideas can be developed for future medical imaging along with a vast array of design strategies.
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Furthermore, the advent of ultrasound scanning has revolutionalized the medical sector. It allows monitoring of miniature-sized objects such as kidney stones and other inaccessible areas like ground pipes of the human cavity through ultrasound, providing better image quality with the tracked region through structured lightning, optical flow, and evaluation of analytical features.
In medical scanning, around 20 percent of the instruments follow ultrasound scanning to capture the required portion in the image. The scanner operation is limited to constant frequency, which results in relatively poor resolution in certain areas and there may be a chance of getting the desired region masked with noisy data. The multidisciplinary research team is working on numerous mathematical models and simulation tools to achieve ultrasound scanning with variable frequency along with speeding up the design process with high precision and accuracy.
There are several steps involved in the designing process to obtain effective results from ultrasound scanning. At the initial stage, high-frequency ultrasound waves are passed on miniaturized pipe organs to capture the input data. These input data obtained are pre-processed through a machine-learning algorithm, where the noise and distortion particles are removed from the input image. This phase is also called as rectification phase. After rectification, the data captured is arranged as per the pixels and processed through a feature extraction stage to extract and compare unique identities present in the image.
At present, the development of novel and efficient methods in ultrasound image processing with wide bandwidth are still at the early stage; its design strategies can give insights into significant improvements in imaging capability. Furthermore, enabling high-resolution 3D printers will assist to achieve effective three-dimensional device designs with faster development cycles.
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