Presentation on theme: "Special Topic In Cardiac MR Imaging Medical Imaging & Image Processing Lab MIIP Center for Informatics Science Nile University, Egypt Abdallah G. Motaal."— Presentation transcript:
Special Topic In Cardiac MR Imaging Medical Imaging & Image Processing Lab MIIP Center for Informatics Science Nile University, Egypt Abdallah G. Motaal Research Assistant, MSc. Candidate Nile University, Egypt
Layout Background Cardiac Magnetic Resonance Imaging Strain Encoded Imaging Theory Anatomy Image Enhancement Strain values correction
Background Magnetic resonance imaging (MRI) is a safe, noninvasive imaging technique that creates detailed images of organs and tissues. MRI uses radio waves and magnets to create images of organs and tissues, unlike computed tomography or conventional x rays, MRI imaging does not use ionizing radiations.
MR Cardiac Imaging Cardiac MR is used to image the heart while it is beating, producing both still and moving pictures of the heart and major blood vessels. Cardiologists use cardiac MR to get images and to look at the structure and function of the different region of the heart. These images can help them decide how best to treat patients with heart problems.
Cardiac Imaging (2) Cardiac MRI is a common test for diagnosing and evaluating a number of diseases and conditions, including: Coronary artery disease Heart valve problems Congenital heart defects Cardiomyopathies Cardiac Tumors Image with a cardiac infarction
What is SENC SENC is a technique that is used to quantify regional function of heart by direct encoding of regional strain of the heart into the acquired image. The technique measure the strain in the direction orthogonal to the image plane. Therefore, in case of short-axis images, only the longitudinal compression of the myocardium from base to apex is measured. On the other hand, circumferential shortening of the myocardium can be measured in the long-axis views of the heart (such as the four-chamber view).
Theory Tagging – Tags are temporary non-invasive markers whose deformations follow the motion of underlying tissue. Diastole Systole Diastole Systole Cardiac image before and after applying SPAMM tagging
Theory (2) Tagging is done in the direction parallel to the image plane. During cardiac cycle, these tag lines follow the motion of the heart. So by knowing the change in the tagging frequency we can get the change in length, so we can calculate the strain. Before Contraction After Contraction
Theory (3) Because of stretching and contraction of the heart, the tagging frequency ranges from wl and wh.
Because of the contraction of the heart, the tagging frequency will change. -w l w l 0 w h -w h S(w) M(z) Myocardium Static Tissue
Color Mapping The normal longitudinal strain ranges from 5 to -25. For qualitative assessment, strain values are represented by colors
Time % Strain
By adding both the L.T and H.T we will get an informative anatomical Image. But the elevated noise leads to poor contrast to noise ratio(CNR). Anatomy Image Enhancement
Bayes classifier was used to increase the CNR. Based on statistical model of both background and tissue signal A.Motaal, M. Al-Attar, N. Osman,A. Fahmy CIBEC 08 IEEE Proceedings
Interleaving Strain Error Correction
L.T 1L.T 2L.T 3L.T 4L.T 5H.T 1H.T 2H.T 3H.T 4H.T 5 T Seconds The Total Time Taken is 2*T Seconds L.T 1L.T 3L.T 5 T Seconds H.T 2H.T 4 The Total Time Taken is only T Seconds Non - Interleaved Interleaved
One-heartbeat Interleaved SENC Sequence trigger Problem: interframes motion of the heart
Correction Algorithm w1w2w3 W nWn-1 Estimate w Derivative Diff < β Compare Wn-1 NO Yes STOP Proposed Correction Algorithm
Phantom Experiment Numerical Computer Simulation was done to generate SENC images with different strain curves, and the proposed algorithms were tested on them
After CorrectionBefore Correction` Time Frame Strain Results
Summary SENC is a technique for measuring regional function of the heart. We developed a Bayesian method to improve the anatomical image reconstructed from SENC. We propose an algorithm to correct strain measurements in interleaved acquisition. The technique enables the reduction of the required timeframes; hence, faster and better quality imaging.