scholarly journals Heuristic detection of blockage in coronary arteries from cardiac magnetic resonance imaging images and predicting heart failure risk using digital image processing

2017 ◽  
Vol 8 (4) ◽  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Heart Failure ◽  
Image Processing ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Digital Image Processing ◽  
Coronary Arteries ◽  
Digital Image ◽  
Resonance Imaging ◽  
Failure Risk

A Cross Sectional Study of Tumors Using Bio-Medical Imaging Modalities

2018 ◽  
Vol 15 (1) ◽  
pp. 66-73 ◽  
Author(s):  
Mashal Tariq ◽  
Ayesha A. Siddiqi ◽  
Ghous Baksh Narejo ◽  
Shehla Andleeb
Keyword(s):  
Magnetic Resonance Imaging ◽  
Image Processing ◽  
Signal Processing ◽  
Magnetic Resonance ◽  
Digital Signal Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Signal ◽  
Imaging Modalities ◽  
Resonance Imaging

Background: Digital Signal Processing (D.S.P) is an evolutionary field. It has a vast variety of applications in all fields. Bio medical engineering has various applications of digital signal processing. Digital Image Processing is one of the branches of signal processing. Medical image modalities proved to be helpful for disease diagnosis. Higher expertise is required in image analysis by medical professional, either doctors or radiologists. Methods: Extensive research is being done and has produced remarkable results. The study is divided into three main parts. The first deals with introduction of mostly used imaging modalities such as, magnetic resonance imaging, x-rays, ultrasound, positron emission tomography and computed tomography. The next section includes explanation of the basic steps of digital image processing are also explained in the paper. Magnetic Resonance imaging modalities is selected for this research paper. Different methods are tested on MRI images. Discussion: Brain images are selected with and without tumor. Solid cum Cystic tumor is opted for the r esearch. Results are discussed and shown. The software used for digital image processing is MATLAB. It has in built functions which are used throughout the study. The study represents the importance of DIP for tumor segmentation and detection. Conclusion: This study provides an initial guideline for researchers from both fields, that is, medicine and engineering. The analyses are shown and discussed in detail through images. This paper shows the significance of image processing platform for tumor detection automation.

Abstract MP31: Left Ventricular Hypertrophy by Electrocardiogram versus Cardiac Magnetic Resonance Imaging as a Predictor for Heart Failure: The MESA Study

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Abdullahi O Oseni ◽  
Waqas T Qureshi ◽  
Mohammed F Almahmoud ◽  
Alain Bertoni ◽  
David A Bluemke ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Heart Failure ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Left Ventricular Hypertrophy ◽  
Cardiac Magnetic Resonance Imaging ◽  
Ventricular Hypertrophy ◽  
Predictive Ability ◽  
Left Ventricular ◽  
Resonance Imaging

Background: Left ventricular hypertrophy (LVH) is an established risk factor for heart failure (HF). However, it is unknown whether LVH detected by electrocardiogram (ECG-LVH) is equivalent to LVH ascertained by cardiac magnetic resonance imaging (MRI-LVH) in terms of prediction of incident HF using risk prediction models like the Framingham Heart Failure Risk Score (FHFRS). Methods: This analysis included 4745 (mean age 61+10 years, 53.5% women, 61.7% non-whites) from the Multi-Ethnic Study of Atherosclerosis who were free of cardiovascular disease at the time of enrollment. ECG-LVH was defined using Cornell’s criteria while MRI-LVH was derived from left ventricular (LV) mass measured by cardiac MRI. Cox proportional hazard regression was used to examine the association between ECG-LVH and MRI-LVH with incident HF. Harrell’s concordance C-index was used to estimate the predictive ability of the FHFRS when either ECG-LVH or MRI-LVH were included as one of its components. The added predictive ability of ECG-LVH and MRI-LVH were investigated using integrated discrimination improvement (IDI) index and relative IDI. Results: ECG-LVH was present in 291(6.1%) while MRI-LVH was present in 499 (10.5%) of the participants. Over a median follow up of 10.4 years, 140 participants developed HF. Both ECG-LVH [HR (95% CI): 2.25(1.38-3.69)] and MRI-LVH [HR (95% CI): 3.80(1.56-5.63)] were associated with an increased risk of HF in multivariable adjusted models (Table 1). The ability of FHFRS to predict HF was improved with MRI-LVH (C-index 0.871, 95% CI: 0.842-0.899) when compared with ECG-LVH (C-index 0.860, 95% CI: 0.833-0.888) (p < 0.0001). To assess the potential clinical utility of using LVH-MRI instead of ECG-LVH, we calculated several measures of reclassification (Table 1), which were consistent with the statistically significantly improved C-statistic with MRI-LVH. Conclusion: Both ECG-LVH and MRI-LVH are predictive of HF when used in the FHFRS. Substituting MRI-LVH for ECG-LVH improves the predictive ability of the FHFRS.

Effects of vitamin D supplementation for six months on cardiac magnetic resonance imaging in mexican patients with heart failure

2018 ◽  
Vol 124 ◽  
pp. 116-117
Author(s):  
Gerardo Mendoza-Lara ◽  
Gustavo Gutiérrez-Del Bosque ◽  
Gerardo García-Rivas ◽  
Luisa Fernanda Pérez-Villarreal ◽  
Bianca Nieblas-Leon ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Heart Failure ◽  
Vitamin D ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Cardiac Magnetic Resonance Imaging ◽  
Vitamin D Supplementation ◽  
Resonance Imaging ◽  
Patients With Heart Failure ◽  
Mexican Patients

Cardiac magnetic resonance imaging in small animal models of human heart failure

2003 ◽  
Vol 7 (3) ◽  
pp. 369-375 ◽  
Author(s):  
M. Nahrendorf ◽  
K.-H. Hiller ◽  
K. Hu ◽  
G. Ertl ◽  
A. Haase ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Heart Failure ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Animal Models ◽  
Human Heart ◽  
Small Animal ◽  
Resonance Imaging ◽  
Human Heart Failure ◽  
Small Animal Models

Role of Cardiac Magnetic Resonance Imaging in Heart Failure

2021 ◽  
Author(s):  
Carla Contaldi ◽  
Santo Dellegrottaglie ◽  
Ciro Mauro ◽  
Francesco Ferrara ◽  
Luigia Romano ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Heart Failure ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Cardiac Magnetic Resonance Imaging ◽  
Resonance Imaging
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