https://issuu.com/ska_telescope/docs/contact_7_-_ska_magazine__pages_/s/11881893
Whether imaging the brain or distant galaxies, the data are not random but contain structure and redundancy. This makes it possible to reconstruct clear images from surprisingly few measurements.
Mathematical tools and artificial intelligence help fill in the blanks—reconstructing incomplete Fourier data in a statistically consistent way.
In both brain imaging and radio astronomy, the data are not random but highly structured, which makes them compressible—and therefore recoverable from limited measurements.
This is the essence of "Compressed Sensing".
A neuroimaging and a cosmology team of CEA (France) joined their efforts through the COSMIC project (Compressed Sensing for Magnetic resonance Imaging and Cosmology). Scientific teamwork led to second-place ranking in the Brain FastMRI Challenge*.
*(led my MetaAI and NYU Langone Health).
We can create or reconstruct an image, such as that of a sphere or a triangle, by "connecting the dots". How many dots do we need to tell the difference between the two? Please refer to this figure. Much less if we have a certain template or model of the object i.e. a spherical or cubical model, and if AI can be used. Less dots or samples to collect means faster scans.
A challenge of image reconstruction was set by the Facebook Artificial Intelligence Research group and a medical MRI center. It consisted of accelerating MRI scans by sampling less points for image reconstruction and by using AI (e.g. neural networks) to connect the dots or fill the gaps. By sampling 4X and 8X less points (undersampling), the scan time was considerably shortened. It is concluded that there are minimal acquisition requirements, when neural networks fill the gaps.
Teams used convolutional neural networks (CNNs), recurrent neural networks (RNNs) and other model architectures.
"Results of the first fastMRI image reconstruction challenge"
AI Meta, 2019-01-12
"Facebook AI accelerates MRI exams"
Healthcare in Europe, 2021-01-21
"FastMRI breakthrough shows AI-accelerated MRIs interchangeable with traditional MRIs"
AI Meta, 2020-08-18