37 Computer Vision News Olivia Sandvold “We want to reduce the number of scans that patients have to take over a period of time,” Olivia tells us. “As we know, CT involves X-rays, and Xrays involve radiation, and we always want to decrease the amount of radiation we supply to the patient. If we have an increased sensitivity to iodine to be able to acquire very high-quality images for diagnosis, then the patient should not have to undergo many additional scans.” From a clinician’s perspective, this represents an improvement over conventional CT or even single instrumentation spectral CT systems, offering greater confidence in quantitative measurements. This newfound precision improves pre- and post-treatment assessments and contributes to establishing standardized medical practices, ultimately benefiting the entire medical community through increased knowledge and accuracy in diagnostics. Olivia says the system encompasses hardware and software advancements over previous setups. She points out that thinking about hardware in combination with software, AI, and machine learning is key. “If we have better underlying measurements from our hardware, we’ll be better at applying different computer vision, downstream image processing, and algorithmic development,” she attests. “The problem is now we have four channels of data, so what do we do with all this data? We’re proposing different software instrumentations and the inclusion of these four channels Top-down view of bench
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