FireANTs, an open-source algorithm, combines AI optimization and geometry to quickly match complex medical images. The new method can accomplish what took weeks in minutes, detecting subtle changes that signal disease or cognitive decline, making it practical for clinical practice.
Researchers are developing an AI assistant to analyze petabytes of imaging data from high-resolution microscopes, which can track cells and molecular interactions in real-time. The goal is to help biologists understand complex biological systems and make new discoveries.
Scientists at Max Born Institute develop technique to generate µJ-level tunable few-fs UV pulses in VUV range. They successfully characterized few-fs pulses tuned between 160 and 190 nm using electron FROG, revealing pulse duration of 2-3 fs.
A collaborative research team led by KAIST has developed a groundbreaking technology that uses advanced optical techniques combined with an AI-based deep learning algorithm to create realistic 3D images of cancer tissue. This breakthrough paves the way for next-generation non-invasive pathological diagnosis.
Professors Scott Acton and Mathews Jacob of UVA's Charles L. Brown Department of Electrical and Computer Engineering were named to the IEEE Signal Processing Society's 2025 Class of Distinguished Lecturers for their groundbreaking work in signal processing, artificial intelligence, and medical imaging.
A novel bio-inspired camera capable of ultra-high-speed imaging and high sensitivity has been developed by KAIST researchers. The camera mimics the visual structure of insect eyes and achieves frame rates thousands of times faster than conventional cameras, while providing clear images in low-light conditions.
The NeuroEXPLORER PET scanner offers exceptional brain PET images with ultra-high sensitivity and resolution, showcasing focal uptake in specific brain nuclei. This technology has the potential to spur advances in treating conditions like Alzheimer's disease, Parkinson's disease, and mental illnesses.
The ultra-high resolution NexGen 7T scanner allows neuroscientists to see functional MRI features 0.4 millimeters across, enabling the study of brain circuitry underlying different diseases with higher spatial resolution. This will help track signals propagating through the brain and reveal underlying causes of developmental disorders.
A new study explores how alpha-synuclein disrupts metabolic processes in neurons. Researchers used NanoSIMS imaging techniques to visualize isotopic variations and found changes in carbon turnover, suggesting increased metabolic demands on affected cells.
A new ultra-high-resolution CT technology has been developed to detect coronary artery disease in high-risk patients, providing a potentially significant benefit for people previously ineligible for noninvasive screening. The technology delivers excellent image quality and accurate diagnosis with high sensitivity and specificity.
A study published in the American Journal of Roentgenology found that reconstruction using BI64 kernel and 0.4-mm slice thickness yielded improved bronchial division identification and pulmonary fissure sharpness without loss in pulmonary vessel sharpness or pathology conspicuity.
A new study using photon-counting CT technology has shown that it can detect more post-COVID-19 lung damage than conventional CT scans, particularly in patients with persistent symptoms. The technology may lead to earlier treatment and better outcomes for those affected by COVID-related lung damage.