Most current fully automated quantitative methods rely on two-dimensional (2D) digital mammography (DM) images, 11 - 14 but in the United States, DM has rapidly been replaced by a ...

When an X-ray beam passes through a patient’s body, the resulting two-dimensional view shows all the bones, tissues and organs along the X-ray’s path as overlapping images. A CT scan takes a series of ...

Automated methods enable the analysis of PET/CT scans (left) to accurately predict tumor location and size (right). Credit: Nature Machine Intelligence (2024). DOI: 10.1038/s42256-024-00912-9 ...

In this retrospective study, the inhalation and exhalation lung CT images and spirometry data were acquired from 8,893 patients from November 2007 to April 2011.

RESEARCHERS at the Hong Kong University of Science and Technology (HKUST) have announced a significant leap forward in medical imaging, developing an artificial intelligence (AI)-powered technology ...

For instance, AI algorithms can accurately predict clinical outcomes on the basis of CT data in cases of traumatic brain injury 21 and cancer. 22 In addition, AI-derived imaging biomarkers can ...

1. A machine and deep learning algorithm from scientists at the IBM Research laboratory in Haifa, Israel, analyzes health records and mammograms to predict the development of breast cancer up to ...

A deep learning–based reconstruction algorithm significantly enhances temporal bone UHR-CT image quality, reducing noise and improving diagnostic precision, a study finds.

[4] Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction. Nature Machine Intelligence (2019).