Assessment of Cardiac Function: First-Pass, Equilibrium Blood Pool, and Gated Myocardial SPECT

2012 ◽  
pp. 195-245
Author(s):  
Elias H. Botvinick ◽  
Nick G. Costouros ◽  
Stephen L. Bacharach ◽  
J. William O’Connell
Keyword(s):  
Cardiac Function ◽  
Blood Pool ◽  
Myocardial Spect ◽  
First Pass ◽  
Gated Myocardial Spect

Assessment of Cardiac Function: First-Pass, Equilibrium Blood Pool, and Gated Myocardial SPECT

2021 ◽  
pp. 261-323
Author(s):  
Elias H. Botvinick ◽  
Nick G. Costouros ◽  
Stephen L. Bacharach ◽  
J. William O’Connell
Keyword(s):  
Cardiac Function ◽  
Blood Pool ◽  
Myocardial Spect ◽  
First Pass ◽  
Gated Myocardial Spect

scholarly journals SHA 004. Diagnostic valve of nitrate enhanced Tc-99m sestamibi gated myocardial spect in myocardial viability: Prospective analysis

2011 ◽  
Vol 23 (3) ◽  
pp. 172
Author(s):  
Zahid Rahman Khan ◽  
Aitizazuddin Syed ◽  
Ali E. Jelly ◽  
A.M. Obaideen ◽  
Shandana Aitizaz ◽  
...  
Keyword(s):  
Myocardial Viability ◽  
Prospective Analysis ◽  
Myocardial Spect ◽  
Gated Myocardial Spect

scholarly journals A Deep Learning Segmentation Approach in Free-Breathing Real-Time Cardiac Magnetic Resonance Imaging

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Fan Yang ◽  
Yan Zhang ◽  
Pinggui Lei ◽  
Lihui Wang ◽  
Yuehong Miao ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Cardiac Function ◽  
Data Augmentation ◽  
Function Analysis ◽  
Free Breathing ◽  
Blood Pool ◽  
Training Time ◽  
Segmentation Approach

Objectives. The purpose of this study was to segment the left ventricle (LV) blood pool, LV myocardium, and right ventricle (RV) blood pool of end-diastole and end-systole frames in free-breathing cardiac magnetic resonance (CMR) imaging. Automatic and accurate segmentation of cardiac structures could reduce the postprocessing time of cardiac function analysis. Method. We proposed a novel deep learning network using a residual block for the segmentation of the heart and a random data augmentation strategy to reduce the training time and the problem of overfitting. Automated cardiac diagnosis challenge (ACDC) data were used for training, and the free-breathing CMR data were used for validation and testing. Results. The average Dice was 0.919 (LV), 0.806 (myocardium), and 0.818 (RV). The average IoU was 0.860 (LV), 0.699 (myocardium), and 0.761 (RV). Conclusions. The proposed method may aid in the segmentation of cardiac images and improves the postprocessing efficiency of cardiac function analysis.

Three-dimensional navigator coronary MRA with the aid of a blood pool agent in pigs: Improved image quality with inclusion of the contrast agent first-pass

2003 ◽  
Vol 18 (4) ◽  
pp. 502-506 ◽  
Author(s):  
Martijn S. Dirksen ◽  
Theodorus A.M. Kaandorp ◽  
Hildo J. Lamb ◽  
J. Doornbos ◽  
Claire Corot ◽  
...  
Keyword(s):  
Image Quality ◽  
Contrast Agent ◽  
Three Dimensional ◽  
Blood Pool ◽  
Blood Pool Agent ◽  
Coronary Mra ◽  
First Pass
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