Scientists have developed an algorithm for rapid, computerized diagnosis of COVID-19, overcoming the limitations of reverse transcription polymerase chain reaction.
Search for: Radiology
A series of procedures have shown how surgeons can use computer-generated augmented reality imaging while operating on patients undergoing reconstructive lower limb surgery.
For the first time, a steerable catheter will give neurosurgeons the ability to steer the device in any direction they want while navigating the brain's arteries and blood vessels.
More than 20 hospitals from across the world together with NVIDIA have used AI to predict Covid patients’ oxygen needs on a global scale.
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.
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.
New research could help surgeons perform liver resections with greater accuracy and deliver improved patient outcomes.
A team of engineers from Rensselaer Polytechnic Institute and clinicians from Massachusetts General Hospital developed a deep learning algorithm that can help assess a patient's risk of cardiovascular disease with the same low-dose computerized tomography (CT) scan used to screen for lung cancer.
Engineers have developed the smallest single-chip system that is a complete functioning electronic circuit - and implantable chip visible only in a microscope.
Trained to see patterns by analyzing thousands of chest X-rays, a computer program predicted with up to 80 percent accuracy which COVID-19 patients would develop life-threatening complications within four days.
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.
The new device can continuously sense levels of virtually any protein or molecule in the blood. The researchers say it could be transformative for disease detection, patient monitoring and biomedical research.
Results of the first clinical trial of 3D printed NP swabs for COVID-19 testing are being presented at the annual meeting RSNA.
Scientists have developed an easy way to make millirobots by coating objects with a glue-like magnetic spray.
Researchers have created a machine learning algorithm that can detect subtle signs of osteoarthritis on an MRI scan taken years before symptoms even begin.
Artificial intelligence is developing at an enormous speed and intelligent instruments will profoundly change surgery and medical interventions.
Researchers have shown that federated learning is successful in the context of brain imaging, by being able to analyze MRI scans of brain tumor patients and distinguish healthy brain tissue from cancerous regions.
Researchers have developed a MR visualisation platform which projects multiple imaging modalities to assist intraoperative surgical guidance.
Scientists have developed an experimental diagnostic test for COVID-19 that can visually detect the presence of the virus in 10 minutes.
Researchers have developed an AI algorithm that can detect and identify different types of brain injuries.
Radiologists are investigating people's medical conditions and pregnancies remotely thanks to an ESA-backed robotic technology.
Researchers have developed a new model that accurately and automatically shows the exact location of mandibular canals.
Researchers are developing a new high-precision radiology system for coronavirus pulmonary involvement.
Ensembles created using models submitted to the RSNA Pediatric Bone Age Machine Learning Challenge convincingly outperformed single-model prediction of bone age.
Radiologists assisted by deep learning based software were better able to detect malignant lung cancers on chest X-rays.
Researchers from Thomas Jefferson University use machine learning on ultrasound images of thyroid nodules to predict risk of malignancy.
Though identifying data typically are removed from medical image files before they are shared for research, a study finds that this may not be enough to protect patient privacy.
An algorithm did better than experts radiologists at finding tiny brain hemorrhages in head scans — an advance that one day may help doctors treat patients with strokes.
An AI tool identified breast cancer with approximately 90 percent accuracy when combined with analysis by radiologists.
Machine learning has the potential to vastly advance medical imaging, particularly CT scanning, by reducing radiation exposure and improving image quality.
Smart speakers that are customarily used in your living room can be programmed to act as an aid to physicians in hospital operating rooms.
Researchers announce critical advances in the use of 3D-printed coronary phantoms with diagnostic software, further developing a non-invasive diagnostic method for Coronary Artery Disease risk assessment.
Researchers have shown that they can use online neurofeedback to modify an individual's arousal state to improve performance in a demanding sensory motor task.
Patients could soon get faster and more accurate diagnoses with new software that can automatically detect signs of diabetes, heart disease and cancer from medical images.
At ECR 2019, researchers talked about the practical applications of mixed realities in medical education and training as well as preprocedural planning and visualization during a surgery.
Royal Philips unveiled a unique mixed reality concept developed together with Microsoft Corp. for the operating room of the future.
A team of experts led by two University of Michigan researchers calls for attention to this shadow record.
UT Southwestern has become the first medical center in Texas to use a robotic tool that allows surgeons to perform complicated operations using just a single incision.
Researchers have developed a system using artificial intelligence to quickly diagnose and classify brain hemorrhages and to provide the basis of its decisions from relatively small image datasets.
Researchers have created a novel 3D printing workflow that allows cardiologists to evaluate how different valve sizes will interact with each patient's unique anatomy, before the medical procedure is actually performed.
SubtlePET’s AI-powered technology allows hospitals and imaging centers to enhance images from faster scans leading to an improved patient experience during imaging procedures.
Medical software that overlays tumour information from MRI scans onto ultrasound images can help guide surgeons conducting biopsies and improve prostate cancer detection.
In a matter of seconds, a new algorithm read chest X-rays for 14 pathologies, performing as well as radiologists in most cases, a Stanford-led study says.
Orthopaedic surgeons can now get their hands on the bones of patients before they reach the operating table – with the help of 3D printing.
Study pinpoints four brain-guided dimensions of psychopathology — mood, psychosis, fear, and disruptive behavior in youth.
Researcher have developed algorithms that analyze patients‘ imaging data and calculate surgical risks. This makes liver cancer surgery safer and easier to plan.
Less expensive and more realistic 3D models of blood vessels may offer alternative to the commercial standard.
VR brings medical images to life on screen, showing interventional radiologists a patient’s unique internal anatomy to help physicians effectively prepare and tailor their approach to complex treatments.