Prediction of low-keV monochromatic images from polyenergetic CT scans for improved automatic detection of pulmonary embolism

Abstract

Detector-based spectral computed tomography is a recent dual-energy CT (DECT) technology that offers the possibility of obtaining spectral information. From this spectral data, different types of images can be derived, amongst others virtual monoenergetic (monoE) images. MonoE images potentially exhibit decreased artifacts, improve contrast, and overall contain lower noise values, making them ideal candidates for better delineation and thus improved diagnostic accuracy of vascular abnormalities.

Publication
ISBI 2021
Constantin Seibold
Constantin Seibold
Team Lead Computer Vision
Rainer Stiefelhagen
Rainer Stiefelhagen
Director Computer Vision for Human-Computer Interaction Lab
Jens Kleesiek
Jens Kleesiek
Professor of Translational Image-guided Oncology