Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
Hosted on MSN

First-ever black hole image sharpened using machine learning

The historic first image of the Messier 87 (M87) supermassive black hole, captured using the Event Horizon Telescope, has been sharped using a machine learning technique called PRIMO. PRIMO is short ...
IEEE

Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review

Abstract: Magnetic Resonance Imaging (MRI) has commonly been used to detect and diagnose brain disease and monitor treatment as non-invasive imaging technology. MRI produces three-dimensional images ...
C&EN

Machine-Learning-Based Automated Schlemm’s Canal Volumetric Segmentation for Optical Coherence Tomography

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Numerous challenges, including the variable anatomy of SC, ...
Frontiers

Multi-interactive feature embedding learning for medical image segmentation

1 School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China 2 School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, ...
Scientific Research Publishing

From U-Net to Swin-Unet Transformers: The Next-Generation Advances in Brain Tumor Segmentation with Deep Learning ()

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
News Medical

New AI model performs medical image segmentation with far less data

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...