scholarly journals Three-dimensional true-FISP imaging of the coronary arteries: Improved contrast with T2-preparation

2002 ◽  
Vol 15 (5) ◽  
pp. 597-602 ◽  
Author(s):  
Steven M. Shea ◽  
Vibhas S. Deshpande ◽  
Yiu-Cho Chung ◽  
Debiao Li
Keyword(s):  
Coronary Arteries ◽  
Three Dimensional ◽  
True Fisp

Breath-hold three-dimensional true-FISP imaging of coronary arteries using asymmetric sampling

2002 ◽  
Vol 15 (4) ◽  
pp. 473-478 ◽  
Author(s):  
Vibhas S. Deshpande ◽  
Steven M. Shea ◽  
Yiu Cho Chung ◽  
Richard M. McCarthy ◽  
J. Paul Finn ◽  
...  
Keyword(s):  
Coronary Arteries ◽  
Three Dimensional ◽  
Breath Hold ◽  
True Fisp

Live Three-Dimensional Transthoracic Echocardiographic Assessment of Coronary Arteries

2003 ◽  
Vol 20 (8) ◽  
pp. 751-754 ◽  
Author(s):  
Srinivas Vengala ◽  
Navin C. Nanda ◽  
Gopal Agrawal ◽  
Vikramjit Singh ◽  
Harvinder S. Dod ◽  
...  
Keyword(s):  
Coronary Arteries ◽  
Three Dimensional ◽  
Echocardiographic Assessment

scholarly journals A computationally efficient approach to segmentation of the aorta and coronary arteries using deep learning

2021 ◽  
Author(s):  
Wing Keung Cheung ◽  
Robert Bell ◽  
Arjun Nair ◽  
Leon Menezies ◽  
Riyaz Patel ◽  
...  
Keyword(s):  
Deep Learning ◽  
Coronary Arteries ◽  
Automatic Segmentation ◽  
Three Dimensional ◽  
Regions Of Interest ◽  
Dice Similarity Coefficient ◽  
Processing Unit ◽  
Two Dimensional ◽  
Computed Tomography Images ◽  
Graphical Processing

AbstractA fully automatic two-dimensional Unet model is proposed to segment aorta and coronary arteries in computed tomography images. Two models are trained to segment two regions of interest, (1) the aorta and the coronary arteries or (2) the coronary arteries alone. Our method achieves 91.20% and 88.80% dice similarity coefficient accuracy on regions of interest 1 and 2 respectively. Compared with a semi-automatic segmentation method, our model performs better when segmenting the coronary arteries alone. The performance of the proposed method is comparable to existing published two-dimensional or three-dimensional deep learning models. Furthermore, the algorithmic and graphical processing unit memory efficiencies are maintained such that the model can be deployed within hospital computer networks where graphical processing units are typically not available.

scholarly journals Multiscale three-dimensional surface reconstruction and surface roughness of porcine left anterior descending coronary arteries

2019 ◽  
Vol 6 (9) ◽  
pp. 190915 ◽  
Author(s):  
Hanna E. Burton ◽  
Rachael Cullinan ◽  
Kyle Jiang ◽  
Daniel M. Espino
Keyword(s):  
Surface Roughness ◽  
Coronary Arteries ◽  
Medical Devices ◽  
Ex Vivo ◽  
Three Dimensional ◽  
Force Microscopy ◽  
Optical Scanning ◽  
Atomic Force ◽  
Reconstructed Surface ◽  
Dimensional Surface

The aim of this study was to investigate the multiscale surface roughness characteristics of coronary arteries, to aid in the development of novel biomaterials and bioinspired medical devices. Porcine left anterior descending coronary arteries were dissected ex vivo , and specimens were chemically fixed and dehydrated for testing. Surface roughness was calculated from three-dimensional reconstructed surface images obtained by optical, scanning electron and atomic force microscopy, ranging in magnification from 10× to 5500×. Circumferential surface roughness decreased with magnification, and microscopy type was found to influence surface roughness values. Longitudinal surface roughness was not affected by magnification or microscopy types within the parameters of this study. This study found that coronary arteries exhibit multiscale characteristics. It also highlights the importance of ensuring consistent microscopy parameters to provide comparable surface roughness values.

Sign in / Sign up

Export Citation Format

Share Document