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Glioblastoma and brain metastasis can have similar clinical symptoms and appearance on MRI, and therefore they require histopathologic results to provide a definitive diagnosis. However, a team of researchers from Spain has found that the combination of MRI radiomics and a machine-learning algorithm can be highly accurate for distinguishing between these brain tumors.

Cinematic rendering was once referred to as "3D on steroids," but it has now become a powerful and effective tool to present pathologies found in postmortem CT for judicial review, according to German researchers.

At the Marie Lannelongue hospital in Paris, advanced imaging techniques and 3D printing are transforming training and practice for vascular procedures. The result has been dramatic improvements in performance and patient outcomes, according to the institution.

Speaking of 3D printing, German researchers have developed a 3D-printed device with built-in pressure sensors that fits around an ultrasound transducer like a shell. They've concluded that it could improve the accuracy of shear-wave elastography measurements for breast imaging and other applications.

A 3D image-analysis software algorithm can identify small changes in the cartilage of knee joints over time that aren't detected using standard x-ray or MRI techniques. Thanks to its improved sensitivity for monitoring knee joint changes, the semiautomated technique could facilitate development of new osteoarthritis treatments, according to a U.K. group.

The COVID-19 pandemic has driven a significant increase in interest in radiomics and texture analysis, according to informatics expert Peter van Ooijen, PhD. Also, advanced visualization toolsets for COVID-19 analysis are among recent bright spots in imaging informatics, according to Steve Holloway of Signify Research. Meanwhile, a radiographer from the U.K. used his home 3D printer to create hundreds of face shields to help fill the need for personal protective equipment in caring for COVID-19 patients.

Researchers have also found that the image quality of 3D whole-heart cardiac MRI can be automatically assessed with an artificial intelligence algorithm.

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