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The State-of-the-Art Echocardiography and Its Viewpoint Classifications
Published in Ayman El-Baz, Jasjit S. Suri, Cardiovascular Imaging and Image Analysis, 2018
Xiaohong W. Gao, Wei Li, Martin Loomes, Yu Qian, Qiang Lin, Liqin Huang, Lianyi Wang
While MR and CT can provide valuable information of the heart, they all fall short of being portable and convenient due to their sizable tunnel-like volumes for a number of situations (e.g., not handy for screening programs in remote regions or in emergency). In addition to the economic concerns, the ability to acquire dynamic information of the moving heart in vivo makes echocardiography (echo) imaging the favorite choice of diagnosis. Applying ultrasonic technique, echo imaging, one of the most widely applied imaging technologies in medicine [10], has been routinely applied in the diagnosis, management, and follow-up of patients with any suspected or known heart diseases. It provides a wealth of useful information, including the size and shape of the heart (internal chamber size quantification), pumping capacity, and the location and extent of any tissue damage. Furthermore, an echocardiogram can also offer physicians other estimates of heart functions such as cardiac output, ejection fraction (EF), and diastolic function.
Cardiovascular system
Published in David A Lisle, Imaging for Students, 2012
Echocardiography may be used to calculate cardiac chamber size and wall thickness, and to diagnose the presence of valvular dysfunction and pericardial effusion. Systolic dysfunction may be diagnosed and quantitated by calculation of left ventricular ejection fraction. Ejection fraction is a measurement of the amount of blood ejected from the left ventricle with systolic contraction. To calculate ejection fraction, the volume of the left ventricle is calculated at the end of diastole (D) and then at the end of systole (S). Left ventricular volume may be calculated by various methods. Figure 3.7 illustrates the modified Simpson’s biplane method. Ejection fraction, expressed as a percentage is calculated by the following formula: D − S/D × 100. Normal values for ejection fraction are 70 per cent ± 7 per cent for males and 65 per cent ± 10 per cent for females.
Contouring Blood Pool Myocardial Gated SPECT Images with a Sequence of Three Techniques Based on Wavelets, Neural Networks, and Fuzzy Logic
Published in Horia-Nicolai Teodorescu, Abraham Kandel, Lakhmi C. Jain, FUZZY and NEURO-FUZZY SYSTEMS in MEDICINE, 2017
Luis Patino, André Constantinesco, Ernest Hirsch
The most informative of the three available data sets is the HSA image set. The main reason is that this latter set can be meaningfully used to calculate the Left Ventricle Ejection Fraction (LVEF). This ratio is defined as the difference between the diastolic and systolic heart volumes, divided by the diastolic heart volume. It is now well known that the left ventricle ejection fraction is one of the most useful parameters describing cardiac function. A normal value of the left ventricle ejection fraction should lie in the range 59%-65%.
Kinematic motion representation in Cine-MRI to support cardiac disease classification
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2022
Alejandra Moreno, Jefferson Rodríguez, Fabio Martínez
Cardiovascular diseases are the leading cause of death around the world, with more than 17.9 million deaths per year, 31% of all deaths worldwide ‘(World Health Organization 2018)’. Heart movement is directly related to cardiac conditions, and therefore result fundamental for diagnosis and following the effectiveness of particular treatments. In clinical routine, cine-MRI sequences bring a powerful observational tool to analyse, explore and quantify cardiac morphological and physiological patterns. For instance, the ejection fraction (EF) is a measure that allows to characterise a wide range of cardiovascular diseases, with a full correspondence of bombing capability during the cardiac cycle ( less than 50% in this index is considered abnormal). Nevertheless, the computation of such measures involves manual delineation of an expert, which result tedious and could be prone to errors. Additionally, such measures could be insufficient to characterise and differentiate complex cardiac behaviours among heart diseases.
W-Net: Novel Deep Supervision for Deep Learning-based Cardiac Magnetic Resonance Imaging Segmentation
Published in IETE Journal of Research, 2022
Kamal Raj Singh, Ambalika Sharma, Girish Kumar Singh
The percentage of blood flowing out of the ventricles’ during contraction is known as ejection fraction (EF). where EDV (end-diastolic volume) and ESV (end-systolic volume) are defined as volume of blood in ventricle in the end-diastole phase, and end-systole phase respectively. In terms of the Dice similarity coefficient, W-Net yields results comparable to the highest performing methodologies [20,21,39] for right ventricle segmentation, as depicted in Table 4. For other segmentation parameters, W-Net delivers significantly better results, as can be seen in Figures 8 and 9. However, for myocardium segmentation, W-Net segmentation results are comparable with two best-performing methodologies [20,21], and superior to another best-performing method [39] for all segmentation parameters, as seen in Table 5. The W-Net approach seems to have a significant limitation in this regard.
Cardiac contractility modulation for the treatment of moderate to severe HF
Published in Expert Review of Medical Devices, 2021
for NYHA Class III HF patients who: Remain symptomatic despite guideline-directed medical therapy.Have a left ventricular ejection fraction ranging from 25% to 45%.Are in normal sinus rhythm.Are not indicated for Cardiac Resynchronization Therapy.