[HTML][HTML] Computed tomography 2.0: new detector technology, AI, and other developments
M Lell, M Kachelrieß - Investigative Radiology, 2023 - journals.lww.com
Computed tomography (CT) dramatically improved the capabilities of diagnostic and
interventional radiology. Starting in the early 1970s, this imaging modality is still evolving …
interventional radiology. Starting in the early 1970s, this imaging modality is still evolving …
[HTML][HTML] Recent advances in artificial intelligence for cardiac CT: Enhancing diagnosis and prognosis prediction
Recent advances in artificial intelligence (AI) for cardiac computed tomography (CT) have
shown great potential in enhancing diagnosis and prognosis prediction in patients with …
shown great potential in enhancing diagnosis and prognosis prediction in patients with …
Milestones in CT: past, present, and future
CH McCollough, PS Rajiah - Radiology, 2023 - pubs.rsna.org
In 1971, the first patient CT examination by Ambrose and Hounsfield paved the way for not
only volumetric imaging of the brain but of the entire body. From the initial 5-minute scan for …
only volumetric imaging of the brain but of the entire body. From the initial 5-minute scan for …
Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy
P Lyu, Z Li, Y Chen, H Wang, N Liu, J Liu, P Zhan… - European …, 2024 - Springer
Objectives To assess image quality and liver metastasis detection of reduced-dose dual-
energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard …
energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard …
[HTML][HTML] Enhanced visualization in endoleak detection through iterative and AI-noise optimized spectral reconstructions
W Kazimierczak, N Kazimierczak, J Wilamowska… - Scientific Reports, 2024 - nature.com
To assess the image quality parameters of dual-energy computed tomography angiography
(DECTA) 40-, and 60 keV virtual monoenergetic images (VMIs) combined with deep …
(DECTA) 40-, and 60 keV virtual monoenergetic images (VMIs) combined with deep …
Deep-learning CT reconstruction in clinical scans of the abdomen: a systematic review and meta-analysis
Objective To perform a systematic literature review and meta-analysis of the two most
common commercially available deep-learning algorithms for CT. Methods We used …
common commercially available deep-learning algorithms for CT. Methods We used …
[HTML][HTML] Artificial intelligence and pediatrics: synthetic knowledge synthesis
The first publication on the use of artificial intelligence (AI) in pediatrics dates back to 1984.
Since then, research on AI in pediatrics has become much more popular, and the number of …
Since then, research on AI in pediatrics has become much more popular, and the number of …
Deep learning–based prediction of percutaneous recanalization in chronic total occlusion using coronary CT angiography
Background CT is helpful in guiding the revascularization of chronic total occlusion (CTO),
but manual prediction scores of percutaneous coronary intervention (PCI) success have …
but manual prediction scores of percutaneous coronary intervention (PCI) success have …
[HTML][HTML] Automated data processing and feature engineering for deep learning and big data applications: a survey
A Mumuni, F Mumuni - Journal of Information and Intelligence, 2024 - Elsevier
Modern approach to artificial intelligence (AI) aims to design algorithms that learn directly
from data. This approach has achieved impressive results and has contributed significantly …
from data. This approach has achieved impressive results and has contributed significantly …
Machine Learning and Deep Learning Applications in Magnetic Particle Imaging
In recent years, magnetic particle imaging (MPI) has emerged as a promising imaging
technique depicting high sensitivity and spatial resolution. It originated in the early 2000s …
technique depicting high sensitivity and spatial resolution. It originated in the early 2000s …