Ika Faizura Mohd Nor

On the Use of Collinear and Triangle Equation for Automatic Segmentation and Boundary Detection of Cardiac Cavity Images

In this chapter, the computational biology of cardiac cavity images is proposed. The method uses collinear and triangle equation algorithms to detect and reconstruct the boundary of the cardiac cavity. The first step involves high boost filter to enhance the high frequency component without affecting the low frequency component. Second, the morphological and thresholding operators are applied to the image to eliminate noise and convert the image into a binary image. Next, the edge detection is performed using the negative Laplacian filter and followed by region filtering. Finally, the collinear and triangle equations are used to detect and reconstruct the more precise cavity boundary. Results obtained have proved that this technique is able to perform better segmentation and detection of the boundary of cardiac cavity from echocardiographic images.

Myocardial motion analysis using optical flow and wavelet decomposition

The abnormalities of myocardial can be predicted quantitatively by analysing visualization of motion estimation in all or part of myocardial segment. To visualize the heart motion on myocardial, ultrasound image is evaluated globally using a differential optical flow technique that recursively applied a set of multi scale ultrasound image. A set of multi scale images is generated using approximation channel of Haar wavelet decomposition. The method was validated and evaluated on the real ultrasound image sequences that were collected from several health and unhealthy volunteers based on the American Heart Association standardization. The method was also compared to other methods using the same of ultrasound images. The result using our proposed algorithm is more accurate than the other methods. The results of myocardial motion estimation are shown in needle view of motion field in all myocardial segments and according to the expert echocardiographic analyzing.

Enhanced optical flow field of left ventricular motion using quasi-Gaussian DCT filter.

Left ventricular motion estimation is very important for diagnosing cardiac abnormality. One of the popular techniques, optical flow technique, promises useful results for motion quantification. However, optical flow technique often failed to provide smooth vector field due to the complexity of cardiac motion and the presence of speckle noise. This chapter proposed a new filtering technique, called quasi-Gaussian discrete cosine transform (QGDCT)-based filter, to enhance the optical flow field for myocardial motion estimation. Even though Gaussian filter and DCT concept have been implemented in other previous researches, this filter introduces a different approach of Gaussian filter model based on high frequency properties of cosine function. The QGDCT is a customized quasi discrete Gaussian filter in which its coefficients are derived from a selected two-dimensional DCT. This filter was implemented before and after the computation of optical flow to reduce the speckle noise and to improve the flow field smoothness, respectively. The algorithm was first validated on synthetic echocardiography image that simulates a contracting myocardium motion. Subsequently, this method was also implemented on clinical echocardiography images. To evaluate the performance of the technique, several quantitative measurements such as magnitude error, angular error, and standard error of measurement are computed and analyzed. The final motion estimation results were in good agreement with the physician manual interpretation.

Acute myocardial infarction following ingestion of a non-selective non-steroidal anti-inflammatory drug

While selective non-steroidal anti-inflammatory drugs, namely cyclo-oxygenase-2 (COX 2) inhibitors, are known to be associated with acute myocardial infarction, little is known about the cardiovascular safety of the non-selective non-steroidal anti-inflammatory drugs. We report the case of a 44-year-old man who developed anaphylactic reaction and acute inferior myocardial infarction following ingestion of a non-selective anti-inflammatory drug, diclofenac sodium. Coronary angiography revealed a large thrombus in the right coronary artery which was partially removed by intracoronary catheter aspiration. Complete resolution of the remaining thrombus was achieved after treatment with an oral anticoagulant.

GLOBAL FEATURE FOR LEFT VENTRICULAR DYSFUNCTION DETECTION BASED ON SHAPE DEFORMATION TRACKING

Left ventricular (LV) shape alteration is closely correlated with cardiac disease and LV function. In this paper, we propose a feature to detect LV dysfunction globally by analyzing the LV shape deformation in systolic contraction. The feature is an index that is extracted from geometric measurement of LV shape such as the length of the long axis, the short axis, and the apical diameter. A framework for computing the features is also proposed that consists of shape model construction and motion estimation of myocardial boundary. The LV shape model is extracted from apical 2 and 4 chamber views of 2D echocardiography. The long axis, the short axis, and the apical diameter were redefined according to the LV shape constructed. An optical flow technique was used to estimate the position of the LV boundary in each frame. The classification of the LV dysfunction was performed using linear discriminant analysis (LDA) and neural networks (NNs). The 2D echocardiography dataset collected from routine clinical check-up were used to validate the proposed method by comparing the computation result and cardiac expert diagnose. Classification performance and statistical analysis, which was performed to discriminate between healthy and diseased data, indicated promising results. The global LV features would provide a strong basis for a global LV function diagnosis and a global cardiac pathology assessment.

Shape deformation descriptor using Fourier analysis

Deformation analysis of left ventricle (LV) shape could provide a new quantitative understanding of its abnormality. Currently, there is established motion estimation that allows accurate tracking of every point on the 2D echocardiography (2DE). This method produces a precise movement vector of each point in 2DE sequence. Analyzing this data using Fourier analysis could produce a new pattern to determine normal and abnormal deformation of LV. Observation of this method was performed on dataset acquired from 10 normal subjects and 10 patients. Two standard views (apical 2 and 4 chamber) were analyzed using a proposed technique to determine a novel insight of deformation. The results obtained are very promising and could be used as reference for future cardiac abnormality detection.

Precise Global Shape Analysis for Left Ventricle Function Assessment

The left ventricular (LV) shape alteration is believed that has close correlation with cardiac disease and LV regional function. In this paper, we propose a set of procedure to evaluate LV shape deformation quantitatively and precisely. The LV myocardial shape of first cardiac cycle (end diastole) is reconstructed using a set of control points manually by expert and then tracked to last cardiac cycle (end systole) using accurate motion estimation. A new global shape parameter is extracted based on the alteration of both of shape in end diastole and end systole. This parameter is a spatial geometry variable on the apical segment of human cardiac. The normal subject and patient data are used to evaluate this procedure. Comparison of the parameter of the global shape analysis on both cases shows a promise result as a new approach to evaluate the regional LV function and such cardiac pathologies.

Myocardial Motion Analysis Using Modified Radial Direction Distribution Based on Magnitude Criteria

Accurate information on myocardial motion is important in diagnosing cardiac abnormalities. In this research, the motion vectors are computed using an optical flow technique and further analyzed based on the magnitude and angle. We utilize a relative motion direction with respect to the center of the cavity, which is more useful for diagnosis because a physician can observe whether a segment is moving to the center or not more clearly. Instead of analizing individual vectors, it is more helpful to visualize the overall trend by performing their angular distribution. However, a common angular distribution considers motions with small and large magnitudes to have only an equal contribution and often fails to represent an accurate motion direction of a segment if there is a wide distribution of vector angles in the respective segment. In this paper, we propose a new method of providing an accurate radial direction profile by modifying the contribution of the motion vectors to the radial direction distribution based on a certain magnitude function. This method has been tested on clinical echocardiography sequences and shown to be successful in providing a more accurate radial direction profile compared with the common angular distribution.