Machine learning to treat COVID-19 patients worldwide
More than 20 hospitals from across the world together with NVIDIA have used AI to predict Covid patients’ oxygen needs on a global scale.
imaging
Robotics expands in spinal surgery
Increasing numbers of hospitals and spine surgeons are adopting robotics and computer navigation, which aim to enhance precision, accuracy and predictability.
Reconstruction of 3D micro-CT images with the help of machine learning
Researchers have used machine learning to help reconstruct three-dimensional micro-CT images of fibrous materials.
Deep learning: classifying brain tumors with a single 3D MRI scan
A team of researchers at Washington University School of Medicine have developed a deep learning model that is capable of classifying a brain tumor as one of six common types using a single 3D MRI scan.
Qubit sensor could revolutionise imaging
Researchers have developed a new type of atomic sensor made of boron nitride. It is based on a qubit in the crystal lattice and is superior to comparable sensors.
Robotic scanner automates diagnostic imaging in the eye
Engineers and ophthalmologists have developed a robotic imaging tool that can automatically detect and scan a patient's eyes for markers of different eye diseases.
Wearable X-ray detector doesn't require heavy metals
Researchers developed a wearable X-ray detector prepared from nontoxic metal-organic frameworks layered between flexible plastic and gold electrodes for high-sensitivity sensing and imaging.
Deep learning-based holographic point-of-care sensor
Researchers have developed a rapid and cost-effective particle agglutination based sensor that is powered by holographic imaging and deep learning
Noninvasive test detects cancer cells
Scientists at have shown that diagnostic nanoparticles could be used to monitor tumor recurrence after treatment or to perform routine cancer screenings.
Deep learning helps visualize X-ray data in 3D
Scientists have leveraged artificial intelligence to train computers to keep up with the massive amounts of X-ray data taken at the Advanced Photon Source.
Artificial intelligence shortcuts introduce bias in cancer treatment
AI tools models are a powerful tool in cancer treatment. However, unless these algorithms are properly calibrated, they can sometimes make inaccurate or biased predictions.
AI measures fat around heart to predict diabetes
Researchers have developed a new artificial intelligence tool that is able to automatically measure the amount of fat around the heart from MRI scan images.
Photos of toasters train AI to detect COVID
Research using machine learning on images of everyday items is improving the accuracy and speed of detecting respiratory diseases, reducing the need for specialist medical expertise.
Cloud computing expands brain sciences
A neuroscientist at University of Texas at Austin wants to democratize the field and support infrastructure.
Neural networks speed up holographic imaging
Researchers have developed a holographic technique that can rapidly reconstruct microscopic images of samples with up to 50-fold acceleration compared to existing methods.
COVID-19: AIs shortcuts lead to misdiagnosis
Researchers discovered that AI models have a tendency to look for shortcuts. In the case of AI-assisted disease detection, these shortcuts could lead to diagnostic errors if deployed in clinical settings.
Deep learning predicts lung cancer risk
An artificial intelligence (AI) program accurately predicts the risk that lung nodules detected on screening CT will become cancerous, according to a new study.
Image fusion method uses AI to improve outcomes
Researchers have developed a new "multi-modal" image fusion method based on supervised deep learning that enhances image clarity, reduces redundant image features and supports batch processing.
Imaging technique to improve bioprinted implants
Scientists have developed a new microscopic imaging approach to take a closer look at 3D printing for developing future patient implants, as well as improved disease modelling and drug screening.
Integrating imaging with deep neural networks
Neural network framework may increase radiologist's confidence in assessing the type of lung cancer on CT scans, informing individualized treatment planning.
Tiny implant for imaging of brain activity
Researchers used nanophotonic technology to develop a brain-implantable tool that can aid in the optical imaging of brain activity.
mhealth: savvy smartphone imaging systems
Development of smartphone-based imaging systems for medicine and healthcare can be optimized by newly published guidelines for holistic assessment.
Portable hybrid gamma camera should improve cancer diagnosis
Scientists have designed a portable 3D imaging device which will improve the treatment and diagnosis of cancer.
New class of quantum dots primed for imaging
A new class of quantum dots opens a range of practical applications, including medical imaging and diagnostics and quantum communication.
Using AI to generate 3D holograms in real-time
A new method called tensor holography could enable the creation of holograms for virtual reality, 3D printing, medical imaging, and more — and it can run on a smartphone.
COVID-19: AI models not yet suitable for clinical use
Researchers have found that out of the more than 300 COVID-19 machine learning models are not suitable for detecting or diagnosing COVID-19 from standard medical imaging.
PEAR: setting nano-imaging in motion
We spoke with Prof. Dominic Zerulla, whose company PEARlabs is developing an imaging technique that sets out to push the boundaries once more – by looking at in-vivo nano-scale processes in motion.
Key task in computer vision gets a boost
A researcher has demonstrated a technique that reduces the computing time for non-rigid point set registration relative to other approaches.
AI identifies precancerous colon polyps
A machine learning algorithm helps accurately differentiate benign and premalignant colorectal polyps on CT colonography scans.
