[HTML][HTML] A review of three-dimensional medical image visualization

R JohnsonChris - Health Data Science, 2022 - spj.science.org
Importance. Medical images are essential for modern medicine and an important research
subject in visualization. However, medical experts are often not aware of the many …

Enhancement of vascular structures in 3D and 2D angiographic images

T Jerman, F Pernuš, B Likar… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
A number of imaging techniques are being used for diagnosis and treatment of vascular
pathologies like stenoses, aneurysms, embolisms, malformations and remodelings, which …

[HTML][HTML] Vessel density map** of small cerebral vessels on 3D high resolution black blood MRI

MS Sarabi, SJ Ma, K Jann, JM Ringman, DJJ Wang… - Neuroimage, 2024 - Elsevier
Small cerebral blood vessels are largely inaccessible to existing clinical in vivo imaging
technologies. This study aims to present a novel analysis pipeline for vessel density …

Beyond Frangi: an improved multiscale vesselness filter

T Jerman, F Pernuš, B Likar… - Medical imaging 2015 …, 2015 - spiedigitallibrary.org
Vascular diseases are among the top three causes of death in the developed countries.
Effective diagnosis of vascular pathologies from angiographic images is therefore very …

Towards radiologist-level cancer risk assessment in CT lung screening using deep learning

S Trajanovski, D Mavroeidis, CL Swisher… - … Medical Imaging and …, 2021 - Elsevier
Purpose Lung cancer is the leading cause of cancer mortality in the US, responsible for
more deaths than breast, prostate, colon and pancreas cancer combined and large …

Motion estimation and correction in cardiac CT angiography images using convolutional neural networks

T Lossau, H Nickisch, T Wissel, R Bippus… - … Medical Imaging and …, 2019 - Elsevier
Cardiac motion artifacts frequently reduce the interpretability of coronary computed
tomography angiography (CCTA) images and potentially lead to misinterpretations or …

Newly developed artificial intelligence algorithm for COVID-19 pneumonia: utility of quantitative CT texture analysis for prediction of favipiravir treatment effect

Y Ohno, K Aoyagi, K Arakita, Y Doi, M Kondo… - Japanese journal of …, 2022 - Springer
Purpose Using CT findings from a prospective, randomized, open-label multicenter trial of
favipiravir treatment of COVID-19 patients, the purpose of this study was to compare the …

A high precision crack classification system using multi-layered image processing and deep belief learning

J Jo, Z Jadidi - Structure and infrastructure engineering, 2020 - Taylor & Francis
Road surfaces experience fatigue stress and loading, which often lead to cracks on the
surface. The cracks might cause serious damage, and therefore, early detection can reduce …

Machine learning for lung CT texture analysis: Improvement of inter-observer agreement for radiological finding classification in patients with pulmonary diseases

Y Ohno, K Aoyagi, D Takenaka, T Yoshikawa… - European journal of …, 2021 - Elsevier
Purpose To evaluate the capability ML-based CT texture analysis for improving
interobserver agreement and accuracy of radiological finding assessment in patients with …

Blob enhancement and visualization for improved intracranial aneurysm detection

T Jerman, F Pernuš, B Likar… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
Several researches have established that the sensitivity of visual assessment of smaller
intracranial aneurysms is not satisfactory. Computer-aided diagnosis based on volume …