PURPOSE: To assess whether image quality differences between SECT (single-energy CT) and DECT (dual-energy CT 70 keV) with equivalent radiation doses result in altered detection and characterization accuracy of liver metastases when using deep learni...
This study aimed to compare the performance of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) in improving image quality and diagnostic performance using virtual monochromatic spectral images ...
IMPORTANCE: Data comparing perioperative outcomes between transvaginal, transabdominal, and laparoscopic/robotic vesicovaginal fistula (VVF) repair are limited but are important for surgical planning and patient counseling.
OBJECTIVES: Deep learning-reconstructed diffusion-weighted imaging (DL-DWI) is an emerging promising time-efficient method for liver evaluation, but analyses regarding different motion compensation strategies are lacking. This study evaluated the qua...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
May 11, 2023
PURPOSE: Although many deep learning-based abdominal multi-organ segmentation networks have been proposed, the various intensity distributions and organ shapes of the CT images from multi-center, multi-phase with various diseases introduce new challe...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.