Improvement of coronary angiography for quantitative coronary analysis by using a computer vision technique

Coronary cine-angiography is an invasive medical image modality, which is widely used in Interventional Cardiology for the detection of stenosis in Coronary arteries. Quantitative coronary analysis is one of the demanding areas in medical imaging and in this study a semi automated quantitative coronary analysis method has been proposed. Direct coronary cineangiogram frames are processed in order to obtain the features of lumen such as, vessel boundary, skeleton and luminal diameter along the vessels’ skeleton as the results. The proposed method consists of four main implementation phases namely, pre-processing, segmentation, vessel path tracking and quantitative analysis. The visual quality of the input frames is enhanced within the pre-processing phase. The proposed segmentation phase is implemented based on a spatial filtering and region growing approach. A clinically important vessel region is processed to detect the vessel boundary and skeleton, which is required as prior knowledge for quantitative analysis. Moreover, the vessel diameter is computed while tracking the vessel skeleton path starting from a given seed. The proposed segmentation method possesses 93.73% mean segmentation accuracy and 0.053 mean fallout rate. Moreover, the proposed quantitative analysis method has been validated for assessing its’ technical supportability using a clinically approved data set. As a result of that, this proposed method computes the vessel diameter along the vessel skeleton in single pixel gap and develops the ability to determine the diameter stenosis as the quantitative analysis results. Additionally, the clinical feasibility of the proposed method has been validated to emphasize the clinical usability. Moreover, this study can be further extended to make clinical decisions on stenosis through the functional significance of the vasculature by using proper medical image modality like biplane angiography

Design for Addressing Data Privacy Issues in Legacy Enterprise Application Integration

Electronic message transfer is the key element in enterprise application integration (EAI) and the privacy of data transferred must be protected by the systems involved in the message transfer from origin to the destination. The recent data privacy regulation such as GDPR (General Data Protection Regulation) has enforced the organizations to ensure the privacy of the personal data handled with obligations to provide visibility and control over to the data owner. Privacy concerns with relevant to sensitive data embedded and transferred through business-to-business (B2B) middleware platforms in enterprise architecture are mostly at risk with the legacy nature of the products and the complexity of system integrations. This poses a great threat and challenge to organizations processing sensitive data over the interconnected systems in complying with regulatory requirements.  This research proposes a solution design to address the data privacy issues related to personal data handled in an enterprise application integration framework. Where electronic messages used to transfer personally identifiable information (PII). The proposal consisting of a design called “Safety Locker” to issue unique tokens related to encrypted PII elements stored in a persistence data storage based on Apache Ignite. While adding REST API interfaces to access the application functionality such as tokenization, de-tokenization, token management and accessing audit logs. The safety locker can run as a standalone application allowing clients to access its functionality remotely utilizing hypertext transfer protocol (HTTP). The design allows the data controllers to ensure the privacy of PII by embedding tokens generated from the application within the electronic messages transferred through interconnected systems. The solution design is evaluated through a proof of concept implementation, which can be adapted, enhanced to apply in EAI implementations

Hierarchical region based template matching technique for global motion reduction of Coronary Cineangiograms

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

Region Growing Segmentation Method for Extracting Vessel Structures from Coronary Cine-angiograms

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.IEEE IEEE Sri Lanka Section Robotics and Automation Section Chapter, IEEE Sri Lanka Sectio

Region growing segmentation method for extracting vessel structures from Coronary Cine-angiograms

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

Reduction of motion disturbances in Coronary Cineangiograms through template matching

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

Study of the dielectric behavior of graphite Oxide Upon Exposure to Chlorine

Graphite Oxide (GO) was synthesized using the Improved Hummer’s Method. After the successful synthesis of GO, it was characterized and its dielectric properties were investigated. The change of dielectric behavior of GO with exposure to chlorine gas (Cl2) was studied. The obtained data were then analyzed to determine the mechanism by which the dielectric properties change. It was established that the gas physisorption is a two-step process of which, one process has linear dependence with time while the other process modeled according to the Langmuir isotherm model and the analysis of the FT-IR spectra of the material before and after being exposed to Cl2 gas also confirmed this phenomenon of physisorption

A Segmentation method for extraction of main arteries from coronary Cine-angiograms

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