AI-Based Cancer Detection Model for Contrast-Enhanced Mammography.

Background: The recent development of deep neural network models for the analysis of breast images has been a breakthrough in computer-aided diagnostics (CAD). Contrast-enhanced mammography (CEM) is a recent mammography modality providing anatomical and functional imaging of the breast. Despite the clinical benefits it could bring, only a few research studies have been conducted around deep-learning (DL) based CAD for CEM, especially because the access to large databases is still limited.

Genome characterisation of norovirus GII.P17-GII.17 detected during a large gastroenteritis outbreak in Romania in 2021.

Norovirus (NoV) is one of the leading causes of acute gastroenteritis worldwide. Genotype GII.P17-G.

Harmonized definition of occupational burnout: A systematic review, semantic analysis, and Delphi consensus in 29 countries.

Objective A consensual definition of occupational burnout is currently lacking. We aimed to harmonize the definition of occupational burnout as a health outcome in medical research and reach a consensus on this definition within the Network on the Coordination and Harmonisation of European Occupational Cohorts (OMEGA-NET). Methods First, we performed a systematic review in MEDLINE, PsycINFO and Embase (January 1990 to August 2018) and a semantic analysis of the available definitions.

Robot guidance of an ultrasound probe toward a 3D region of interest detected through X-ray mammography.

Purpose: This research is situated in the context of breast cancer detection where the standard procedure is the succession of an initial mammography (MX) examination and a supplementary ultrasound (US) scan. One major difficulty of this procedure results from the fact that breast geometry changes between both examinations due to different patient's positions. The proposed system facilitates this combined examination by keeping the breast geometry and by adding a US probe guidance robot to the mammography system.

Anatomical noise in contrast-enhanced digital mammography. Part II. Dual-energy imaging.

Purpose: Dual-energy (DE) contrast-enhanced digital mammography (CEDM) uses an iodinated contrast agent in combination with digital mammography (DM) to evaluate lesions on the basis of tumor angiogenesis. In DE imaging, low-energy (LE) and high-energy (HE) images are acquired after contrast administration and their logarithms are subtracted to cancel the appearance of normal breast tissue. Often there is incomplete signal cancellation in the subtracted images, creating a background "clutter" that can impair lesion detection.