Today, 7 August 2010, 12.30 pm.
Mr Tajul, Dr Rabiah, Chun Yee, Wei Chiet, Chin Yee, Mei Yee and me, discussing the post system development, code, scope and how to proceed with the task. We agree to meet again next Saturday.
We invite postgraduate candidate (PhD and MSc) to joint CASD research as a team and work together towards its goal to assist medical expert. Research area under CASD project include Medical Image Analysis, Multimedia Database, Computer Graphics, Data Visualization, Augmented Reality and Holographics Interaction. The expected output are Cardiovascular Information System, Heart Diseases Diagnostic Systems, Computer Assisted Medical Research and 3D Medical Visualization.
Saturday, August 7, 2010
Wednesday, July 21, 2010
PRPI 2010
Congratulation to Hasan and his team for winning gold medal in PRPI 2010.
Next step will enhance the 3D, fitting it with polynomial fitting, deploying the directive partial derivative and identify the sudden changes. At the same time, enhance the voice activation platform and database design to suit the main system.
Next step will enhance the 3D, fitting it with polynomial fitting, deploying the directive partial derivative and identify the sudden changes. At the same time, enhance the voice activation platform and database design to suit the main system.
Thursday, July 15, 2010
At IT-Healthcare Exhibition
Can be seen here, Mrs Puteri Suhaiza, Mrs Rabiah Abdul Kadir, Mrs Lilly Suriani and Mrs Rahmita Wirza infront of Clinical Research Centre booth. We were interested with the One Stop Centre and would like to know what information that this centre can provide. Most probably our next visit will be this centre.
This is a poster in the CRC booth. Listed were academics' publication in highly impact factor journal.
CRC poster.
We were interested with OT management system even though not within our project's scope.
Thursday, June 10, 2010
An Improved Seed Point Detection Algorithm for Centerline Tracing in Coronary Angiograms
We presents a new method to detect initial seed points for automatic tracing of the vessel center lines in coronary angiograms. Vessel tracing algorithms are known to be fast and efficient among several feature extraction methods. However, most of them suffer from incomplete results due to inappropriate trade-off between the completeness of seed point detection and computational efficiency. Imposing strict validation rules decreases the number of background traces, but results in more false negatives and more computation time. We show that using the geometrical properties of gradient vectors calculated at vessel boundary points as a validation criterion, improves the performance of the seed point detection algorithm. The results illustrate that the proposed method improves upon the prior method in both performance and computation time.continue-->
Tuesday, June 8, 2010
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
Echocardiogram has become an important diagnostic tool in modern cardiology. Although this imaging modality is the most widely used to evaluate regional left ventricular function, it allows non-invasive real-time visualization of left ventricular motion. Evaluation of the left ventricular function based on subjective experience-dependent visual interpretation of dynamic images of echocardiograph. Unfortunately echocardiograph is notoriously difficult to interpret even for the best physicians where they could misdiagnose the heart disease. Hence there is a tremendous need for an automated technique that can provide objective diagnostic assistance, particularly to the less-experienced cardiologist.
In this study, the team address the task of building a computer aided diagnosis system that can detect LV motion abnormalities from echocardiograph. The team work based on the anatomical structure of the left ventricular wall in short axis echocardiograph and the team will use the wall thickening as a parameter to evaluate a profile for the regional myocardial function in normal conditions. Continue -->
In this study, the team address the task of building a computer aided diagnosis system that can detect LV motion abnormalities from echocardiograph. The team work based on the anatomical structure of the left ventricular wall in short axis echocardiograph and the team will use the wall thickening as a parameter to evaluate a profile for the regional myocardial function in normal conditions. Continue -->
Saturday, June 5, 2010
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