What the Tech? Medical Imaging Injects New Impetus into AI-based Medical Diagnosis
Medical imaging, the process of creating visual representation of the interior of a body for clinical analysis and medical intervention, plays in an important part in efficient disease diagnosis. Among various types of medical imaging, tomography, or imaging by sections, is the best known, Its main methods are X-ray computed tomography (CT), positron emission tomography (PET) and magnetic resonance imaging (MRI). Although traditional MRIs and CTs are commonly used in body scans, they are being improved to unleash greater potential and more accurate and efficient AI-medical diagnosis. This article will introduce the way AI technology is shaping and improving medical imaging and the contributions made by CT scans and MRI.
CT scans
Matrix AI Network has been leveraging AI technology to advance its medical projects, like small cell lung cancer (SCLC) diagnosis and rib fracture diagnosis based on CT scans. For the projects above, Matrix AI Network has addressed two major problems respectively: one is to better identify SCLC cells in high-resolution CT scans (20000 x 20000) by analyzing macro- and micro-data, while the other is to greatly improve the accuracy and efficiency of diagnosis and treatment by resourcing the original CT scan and generating a 3D image.
MRI
Microsoft’s Quantum team cooperates with Case Western Reserve University to enhance their approach to detecting cancerous tumors and then improving accuracy of MRI results in less time by introducing an approach named magnetic resonance fingerprinting. This uses a constantly varying sequence of pulses to get a single, unified exam.
Facebook and NYU School of Medicine have launched a collaborative research project named fastMRI, making MRI scans up to 10 times faster. If this effort is successful, it will make MRI technology available to more people, expanding access to this key diagnostic tool.
A Canadian research team successfully communicated with vegetative state patients via MRI.
With such contributions to the current AI-medical diagnosis, medical imaging is beyond doubt valuable. As it employs the latest form of high-quality data, how to explore its potential in the fields of blockchain and AI technology becomes the next question. Based on the current rib fracture and SCLC projects, Matrix AI Network has been applying the visual data into AI model training, forming a virtuous circle where medical diagnosis systems and AI-medical platforms can be constantly improved.
Matrix AI Network leverages the latest AI technology to deliver on the promise of blockchain.
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