Radiology has always been an area at the cutting edge of digitization.
From virtual reality to machine learning, there are ways to apply some of the biggest concepts in technology right now to what’s happening in the medical field.
We’ll be at the Radiological Society of North America’s conference in Chicago for the next few days, checking out all the cutting-edge technology coming on the scene.
Here are some of the innovations and trends we’re looking forward to seeing in action.
Virtual reality could help us get a better look at fetuses.
In the near future, we might be using a virtual reality headset to see a developing fetus instead of the traditional ultrasound.
The technology, still experimental, has been used on 30 pregnancies in Brazil. The 3D image is compiled using both MRI and ultrasound technology then uses an Oculus Rift 2 to get an even clearer picture of what’s happening. With the model, researchers can see the exterior of the fetus, along with inside the respiratory tract so that doctors could ideally see abnormalities.
“The 3D fetal models combined with virtual reality immersive technologies may improve our understanding of fetal anatomical characteristics and can be used for educational purposes and as a method for parents to visualize their unborn baby,” study author Dr. Heron Werner Jr. said in a release.
The technology, while novel, might also be too expensive for use in every pregnancy compared to traditional ultrasound.
3D printing is helping researchers better understand how Zika affects baby’s brains.
We’re still learning about the effects the Zika virus has on the brain, especially in babies who contract the virus before birth. And imaging is integral to increasing that understanding and improving treatments. In new studies being presented at the RSNA conference, researchers used CT scans, MRIs, ultrasounds, and 3-D modeling to get a better picture.
Thanks to these technologies, the researchers were able to figure out a few key things, including more evidence that Zika can cause brain damage in babies with and without microcephaly, something that other studies have been able to show as well.
Machine learning could help dermatologists better screen for cancer.
Beyond putting together better images, researchers are also trying to figure out if there’s a way we could analyze these images in a smarter way, with the help of machine learning.
One area where that’s being explored is in skin cancer. One study released by IBM suggested that the company’s computer could better identify melanoma than dermatologists, but we’ll have to wait and see more validation before deciding the extent to which machine learning could help with skin cancer screening.
Machine learning could also enhance how doctors read X-Rays.
REUTERS/ Jean-Paul Pelissier
In the medical world, machine learning and radiology seem to be a hot combination. GE is partnering with UC San Francisco over the next three years to help doctors determine which results need more attention, reports Fast Company. One of the projects aims to shorten the time between reading an X-ray and giving potentially lifesaving treatment.
And they’re not the only ones jumping the space. Watson Health said in June that it’s partnering with more than 15 hospitals and companies using imaging technology to see how “cognitive imaging” works in the real world. The collaboration will help Watson Health figure out what works and what doesn’t before they launch the service, expected in 2017.
Watson Health sees these imaging tools as a type of physician assistant, with the hope that it will seamlessly help the doctors do their jobs better.
“Patients may never know, but the clinician certainly will,” said Anne Le Grand vice president of imaging at Watson Health told Business Insider in June. Like any other new technology, this machine learning assistance will have to prove that it works better than the way radiologists do it now.
Improving existing technologies to make them more sustainable.
The imaging technologies used around the world today use a lot of critical natural resources. For example, there is only so much helium (used in MRI machines) in the world, so finding ways to conserve that element will be key.
This sustainability could happen either by limiting the number of exams we perform, or by creating more sustainable machines. A review published earlier this year in the World Journal of Science, Technology and Sustainable Development found that “adoption of sustainable diagnostic radiology by many countries in Europe and the UK helps to provide imaging services efficiently and effectively, with simultaneous preservation of the natural resources, patient health and environment much better than before.”
Did we miss any great innovations happening in radiology? Let us know at email@example.com.