Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

Abstract: Deep learning-based reconstruction for MRI has attracted attention as an effective method for reducing reconstruction time and improving reconstructed image quality. In an application of ...

WPI researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict Alzheimer's disease with nearly 93% accuracy. Their research, published in the ...

After age 40, we may all have busted-looking shoulders. But that doesn’t mean anything is wrong. In a study of hundreds of people, MRI images showed that nearly every person scanned had frayed, torn ...

High-resolution 7.0 T MRI of the eye and orbit of a volunteer that shows in great detail the anterior cranial structures, including the extraocular muscles, optic nerve, and a cyst adjacent (yellow ...

As shown below, the inferred masks predicted by our segmentation model trained by the dataset appear similar to the ground truth masks. This repository contains a curated and enhanced version of brain ...

Performance of a blood-biomarker test for early detection of pancreatic ductal adenocarcinoma (PDAC) across all stages of disease versus a mixed control population. This is an ASCO Meeting Abstract ...

Emi Gal’s work is personal. He has more than 200 moles on his body, which puts him in the highest risk category for skin cancer, and his mother died from metastatic disease that she discovered too ...

The Tyger framework enables faster, more accessible medical imaging by streaming raw data to the cloud for accelerated reconstruction—reducing patient wait times and discomfort—while empowering ...

GE HealthCare has received FDA Premarket Authorization for Pristina Recon DL, an innovative 3D mammography reconstruction application. Powered by artificial intelligence (AI), Pristina Recon DL ...