Browsing by Author "Constantine, GR"

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    Hierarchical region based template matching technique for global motion reduction of Coronary Cineangiograms
    Kulathilake, KASH; Ranathunga, L; Constantine, GR; Abdullah, NA
    The Coronary Cineangiogram (CCA) is an invasive medical image modality which is used to determine the stenosis in the Coronary Arteries. The global motion occurring due to the heart beat makes great disturbance to obtain the visual alignment among the vessel structure shown in the CCA frames. Therefore, the recorded vessel structure’s position in CCA varies within the frame sequence. This paper describes a hierarchical region based template matching technique to reconstruct the CCA by reducing the global motion artifacts. This proposed motion reduction technique is efficient and it reconstructs the CCA by reducing the background motion as desired. Experimental results of this method have shown its’ ability to maintain the visual alignment of the internal blood flow among the frames.
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    item: Article-Abstract
    Reduction of motion disturbances in Coronary Cineangiograms through template matching
    Kulathilake, KASH; Ranathunga, L; Constantine, GR; Abdullah, NA
    The coronary cineangiogram (CCA) is an invasive medical image modality which is used to determine the stenosis in Coronary Arteries. The motion artifacts occurring due to the heart pulse makes great disturbance to visualize a stable contrast agent flow within the vessel structure of CCA and it negatively affects to quantify the stenosis based on the functional significance within the arterial flow. This paper describes an application of template matching to reconstruct the CCA by reducing the global motion artifacts. The Normalized Correlation Coefficient (NCC) method has been used for the template matching because, it reports the lowest false matching occurrences. Further, the NCC technique has 99.5% accuracy and demonstrates its ability to maintain the visual correlation of the internal blood flow among the frames. Producing Motion eliminated CCA to maintain the visual correlation of arterial flow is an improvement of angiography technique which can be useful for advanced processing.
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    item: Conference-Full-text
    Region Growing Segmentation Method for Extracting Vessel Structures from Coronary Cine-angiograms
    (2015-08-04) Kulathilake, KASH; Ranathunga, L; Constantine, GR; Abdullah, NA
    The coronary cine-angiogram (CCA) is an invasive medical image modality which is used to determine the luminal obstructions or stenosis in the Coronary Arteries (CA). CCA based quantitative assessment of vascular morphology is a demanding area in medical diagnosis and segmentation of blood vessels in CCAs is one of the mandatory step in this endeavor. The accurate segmentation of CAs in Angiogram is a challenging task due to various reported reasons. In order to overcome this challenge, we proposed a region growing segmentation method which implements using morphological image processing operations and flood fill method. It can extract the boundary of main CA visualized in the processed CCA completely. The result of the proposed method reveals that this proposed segmentation method possesses 90.89% accuracy to segment the CAs related to the selected Angiography views. This segmentation results can be further enhanced to determine the functional severity of the CA and this study laid the foundation to improve the Angiography based diagnosis technique.
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    item: Conference-Abstract
    Region growing segmentation method for extracting vessel structures from Coronary Cine-angiograms
    Kulathilake, KASH; Ranathunga, L; Constantine, GR; Abdullah, NA
    The coronary cine-angiogram (CCA) is an invasive medical image modality which is used to determine the luminal obstructions or stenosis in the Coronary Arteries (CA). CCA based quantitative assessment of vascular morphology is a demanding area in medical diagnosis and segmentation of blood vessels in CCAs is one of the mandatory step in this endeavor.The accurate segmentation of CAs in Angiogram is a challenging task due to various reported reasons. In order to overcome this challenge, we proposed a region growing segmentation method which implements using morphological image processing operations and flood fill method. It can extract the boundary of main CA visualized in the processed CCA completely. The result of the proposed method reveals that this proposed segmentation method possesses 90.89% accuracy to segment the CAs related to the selected Angiography views. This segmentation results can be further enhanced to determine the functional severity of the CA and this study laid the foundation to improve the Angiography based diagnosis technique.
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    item: Conference-Abstract
    A Segmentation method for extraction of main arteries from coronary Cine-angiograms
    Kulathilake, KASH; Ranathunga, L; Constantine, GR; Abdullah, NA
    Coronary Cine- Angiogram (CCA) based subjective assessment of vascular malfunction is a preliminary diagnostic method in Cardiac clinical procedures. Even though there are many other medical image modalities available, improving the CCA method to objectively detect and assess the stenosis is a cost effective approach in Cardiac clinical procedures. Segmentation of Coronary Arteries (CA) is a basic and challenging area in such an endeavour. Hence, in this study we proposed a segmentation method to extract the major areas of CA based on Frangi's vessel enhancement filter and region growing segmentation method called flood fill. Experimental results of our proposed segmentation method have clearly proven its ability to extract the main CA almost completely. Moreover this proposed segmentation method possesses 93.73% average segmentation accuracy. Further, it detects the vessel path lines of the segmented frames using a thinning algorithm. The results obtained from this proposed segmentation method can be further enhanced to determine the functional severity of the CA and this study lays a foundation to improve the Coronary Angiogram image modality to do objective diagnosis of stenosis in future.