From good to great / Mohd Zamrin Dimon.

It is indeed a pleasure and an honour for me to pen this editorial as I embark on this journey as the new Editorin-Chief for the Journal of Health and Clinical Sciences, the official journal for the Faculty of Medicine Universiti Teknologi MARA (UiTM). I would like to express my gratitude and appreciation to all the members of the Editorial Board for initiating and subsequently driving this journal to its current position. I am pleased that the journal has met its planned timeline in achieving the due recognition and rise to greater heights in the new future. As the official journal of the faculty, it has an important role in supporting the faculty to achieve its goal as a Centre of Excellence in medicine

Vessel centerline extraction using new center of gravity equations

The extraction and tracking of the vessels and their centerlines of coronary artery vessels in 2D and 3D angiograms has been vital part of many clinical analysis studies. This paper presents a new approach to extract the centerlines of vessels using novel center of gravity equations. The new equations depend on the intensity value as their main factor to track the vessels and by applying the center of gravity technique it can lead to centerline extraction. The new algorithm is called New Center of Gravity (NCOG). NCOG algorithm consists of four stages. First stage is angiogram partitioning using Recursive data structure technique. The second stage is to calculate the gray pixels in each partition and compare them with a threshold value (T). The third stage is center of gravity (COG) calculation. The fourth and last stage is connecting the final COG points by lines. The algorithm using the new COG equations were applied on a raw of clinical data and the results showed high robustness in extract the centerlines of vessels. We can conclude that our approach is robust, time saving, and helpful tool in surgery management and scientific researches

The Use of Metamodel-based Approach for Designing Healthcare Applications

Recently, the use of Model-Driven Engineering (MDE) via metamodeling approach is gaining more attention for software applications development. The community from the healthcare domain also attempts to employ the metamodel approach for producing quality healthcare applications. Healthcare applications have become an imperative in every attempt to improve healthcare management. Numerous studies reported that the healthcare domain is seen as a complex and unique domain, which involves dynamic characteristics. In addition, it is widely recognized that the increase of information exchange in the healthcare domain is caused by the diversity of healthcare data. This has led to the increase use of information technologies in the healthcare industry so as to enhance the healthcare delivery process via healthcare applications. However, the complexity of healthcare information leads to ineffective models and design of healthcare applications. Modeling the healthcare processes and developing healthcare applications are challenging tasks.  Hence, the advances of MDE have influenced the use of the metamodeling technique in the development of healthcare applications. Various metamodels are developed as a solution to provide a clear healthcare process model and a correct healthcare application. The aim of this paper is to analyse the use of the metamodel-based approach in designing healthcare applications. We believe that the metamodel-based approach would improve the development of healthcare applications.&nbsp

Three dimension reconstruction of coronary artery tree using single-view cineangiogram

Whereas most of the conventional techniques propose using multiview cineangiograms to reconstruct 3D objects this article proposes to integrate a Three Dimension(3D) model of the coronary artery tree using a standard single-view cineangiogram. Splitting the cineangiograms into non-sequenced and different angle views is how the data is supplied in this method. Each single view can be used to reconstruct a robust 3D model of the coronary artery from that angle of view. Although the dynamic variations of blood vessels curvature have been difficult to study in Two Dimension (2D) angiograms, there is both experimental and clinical evidence showing that 3D coronary reconstruction is very useful for surgery planning and clinical study. Approach: The algorithm has three stages. The first stage is the vessel extraction and labeling for each view for the purpose of constructing the 3D model, while in the second stage, the vessels information (x, y and z) will be saved in a data file to be forwarded to the next stage. Finally, we input the x, y and z of a specific coronary artery tree to the OPENGL library included in the software, which we developed and called Fast 3D (F3D) and which is displayed in R3. Results: Experimental evaluation has been done to clinical raw data sets where the experimental results revealed that the proposed algorithm has a robust 3D output. Conclusion: Results showed that our proposed algorithm has high robustness for a variety of image resolutions and voxel anisotropy

A new human heart vessel identification, segmentation and 3D reconstruction mechanism

Background: The identification and segmentation of inhomogeneous image regions is one of the most challenging issues nowadays. The surface vessels of the human heart are important for the surgeons to locate the region where to perform the surgery and to avoid surgical injuries. In addition, such identification, segmentation, and visualisation helps novice surgeons in the training phase of cardiac surgery. Methods: This article introduces a new mechanism for identifying the position of vessels leading to the performance of surgery by enhancement of the input image. In addition, develop a 3D vessel reconstruction out of a single-view of a real human heart colour image obtained during open-heart surgery. Results: Reduces the time required for locating the vessel region of interest (ROI). The vessel ROI must appear clearly for the surgeons. Furthermore, reduces the time required for training cardiac surgery of the novice surgeons. The 94.42% accuracy rate of the proposed vessel segmentation method using RGB colour space compares to other colour spaces. Conclusions: The advantage of this mechanism is to help the surgeons to perform surgery in less time, avoid surgical errors, and to reduce surgical effort. Moreover, the proposed technique can reconstruct the 3D vessel model from a single image to facilitate learning of the heart anatomy as well as training of cardiac surgery for the novice surgeons. Furthermore, extensive experiments have been conducted which reveal the superior performance of the proposed mechanism compared to the state of the art methods

A fast and accurate method for automatic coronary arterial tree extraction in angiograms

Coronary arterial tree extraction in angiograms is an essential component of each cardiac image processing system. Once physicians decide to check up coronary arteries from x-ray angiograms, extraction must be done precisely, fast, automatically and including whole arterial tree to help diagnosis or treatment during the cardiac surgical operation. This application is very helpful for the surgeon on deciding the target vessels prior to coronary artery bypass graft surgery. Some techniques and algorithms are proposed for extracting coronary arteries in angiograms. However, most of them suffer from some disadvantages such as time complexity, low accuracy, extracting only parts of main arteries instead of the full coronary arterial tree, need manual segmentation, appearance of artifacts and so forth. This study presents a new method for extracting whole coronary arterial tree in angiography images using Starlet wavelet transform. To this end, firstly we remove noise from raw angiograms and then sharpen the coronary arteries. Then coronary arterial tree is extracted by applying a modified Starlet wavelet transform and afterwards the residual noises and artifacts are cleaned. For evaluation, we measure proposed method performance on our created data set from 4932 Left Coronary Artery (LCA) and Right Coronary Artery (RCA) angiograms and compared with some state-of-the-art approaches. The proposed method shows much higher accuracy 96% for LCA and 97% for RCA, higher sensitivity 86% for LCA and 89% for RCA, higher specificity 98% for LCA and 99% for RCA and also higher precision 87% for LCA and 93% for RCA angiograms

Three-dimension coronary artery tree curvature confirmation

Problem statement: Three-Dimension (3D) reconstruction is one of the vital and robust tools that provide aid in many fields, especially medicine. This article is about 3D shape similarity and it presents a comparison approach between principal curvature methods of 3D output. Our approach follows the concept of using the gray scale value as the z dimension and the other approach is a standard one. A comparison of the curvature of the 3D outputs will be made between the standard approach and our proposed one to prove its correctness. We propose to use the standard deviation technique to compare the output features of the 3D coronary artery trees. We applied a standard approach of 3D shape similarity and compared the features with ours. The standard approach was published in 1998 as a study comparing certain 3D curvature measurement algorithms. Approach: Our approach consists of three major steps: (1) Apply the paraboloid fitting technique from the standard approach; (2) Apply the 3D reconstruction algorithm proposed in this research on the same data in step (1) and (3) Apply the Standard Deviation technique on both outputs from (1) and (2) and compare the outputs. Results: Experimental evaluation has been done on clinical raw data sets where the experimental results revealed that both outputs are totally matched. Conclusion: The match in the output refers to the correctness of the proposed 3D output and subsequently its coronary artery tree curvature as well

Automatic detection of the end-diastolic and end-systolic from 4D echocardiographics images

Accurate detection of the End-Diastolic (ED) and End-Systolic (ES) frames of a cardiac cycle are significant factors that may affect the accuracy of abnormality assessment of a ventricle. This process is a routine step of the ventricle assessment procedure as most of the time in clinical reports many parameters are measured in these two frames to help in diagnosing and dissection making. According to the previous works the process of detecting the ED and ES remains a challenge in that the ED and ES frames for the cavity are usually determined manually by review of individual image phases of the cavity and/or tracking the tricuspid valve. The proposed algorithm aims to automatically determine the ED and ES frames from the four Dimensional Echocardiographic images (4DE) of the Right Ventricle (RV) from one cardiac cycle. By computing the area of three slices along one cardiac cycle and selecting the maximum area as the ED frame and the minimum area as the ES frame. This method gives an accurate determination for the ED and ES frames, hence avoid the need for time consuming, expert contributions during the process of computing the cavity stroke volume

Quantitative detection of left ventricular wall motion abnormality by two-dimensional echocardiography

Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis

Single image reconstruction of human heart surface with specular reflection remover

3D reconstruction with specular reflection remover is one of the vital and robust tools that provide aid in many fields, especially medical filed. This article presents a novel method for reconstruction a real human heart surface from a single view image with a remover specular reflection while keeping the image structure. Reconstruct a heart model from numbers of real images is difficult task and time consuming especially involve reflections, resulted from moisten of the human heart surface. In this paper, we propose a novel method for reconstruct a human heart from a single image while detecting and correcting the specular reflection. The process start with acquired the real heart image by a digital camera in cardiac surgery. Second, processed the image to extract the x, y, and z axes for each pixel and automatic detect the specularities using the difference of the maximum blue color channel and standard deviation of the RGB color channels. Later proceeded with the correction process by the L-shape inverse (Γ) to recover losing information saturated by lights in the operation theater. Finally, the reconstructed of the 3D model for the heart. Experimental results on the heart images show the efficiency of the proposed method comparing to the existing methods