Algorithm on tracing the boundary of medical images using abstract cellular complex

Krishnan, G. Sai Sundara; Vijaya, N.

doi:10.1109/mvip.2012.6428780

Cited by 4 publications

(5 citation statements)

References 6 publications

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“…Boundary tracing algorithm [17] traces the boundary of an image and semifrontier tracing algorithm [19] extracts the semi-frontier of an image. The semi-frontier elements are generally a small subset of the total number of elements that represent a boundary.…”

Section: Resultsmentioning

confidence: 99%

“…In this section, Semi-Frontier tracing algorithm is compared with Boundary tracing algorithm [17] on the basis of various important factors. The various important factors of the comparison are as follows:…”

Section: Comparison With Boundary Tracing Algorithmmentioning

confidence: 99%

“…Further, a new algorithm for tracing the semi-frontier of an image using Kovalevsky's chain code is introduced. Finally, a comparative study between the semi-frontier tracing algorithm and boundary tracing [17] algorithm on various images is presented.…”

Section: Introductionmentioning

confidence: 99%

“…An efficient algorithm for tracing the semi-frontier of an image is introduced and is implemented through MATLAB. Finally, the semi-frontier algorithm is compared with the boundary tracing algorithm [G. Sai Sundara Krishnan, 2012]. …”

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confidence: 99%

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Boundary Detection Algorithm Based on Semi-Subcomplexes

Krishnan¹,

Vijaya²

2016

Int. J. of Pure and Appl. Math.

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In this paper, the concept of semi-open subcomplexes in abstract cellular complex is introduced and some of their properties are investigated by describing the notions of semifrontier, semi-interior and semi-closure. An efficient algorithm for tracing the semi-frontier of an image is introduced and is implemented through MATLAB. Finally, the semi-frontier algorithm is compared with the boundary tracing algorithm [G. Sai Sundara Krishnan, 2012].

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Section: Resultsmentioning

confidence: 99%

Section: Comparison With Boundary Tracing Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Boundary Detection Algorithm Based on Semi-Subcomplexes

Krishnan¹,

Vijaya²

2016

Int. J. of Pure and Appl. Math.

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“…The geodesic active region model presented by Nikos and et all [23], who integrates boundary-based with region-based active contour approaches, is more effective than region-based snake segmentation methods, because prior knowledge about ROI is introduced. The important 3 | P a g e problems in the region-based approaches include the design of region-based models.…”

Section: Literature Reviewmentioning

confidence: 99%

Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique

Alam

Shakir

Hossain

et al. 2018

Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications

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AcknowledgementsIn the beginning, we would like to thank the almighty Allah for enabling us to conduct our research and allowing us to successfully conclude it.Moreover, we would like to express our gratitude and appreciation to all those outstanding person who collaborated us throughout this research period. First of all, special thanks are due to Assistant Professor Dr. Md. Ashraful Alam, our thesis supervisor. He gave us invaluable advice, provided insight and helped us to implement this research work by providing helpful instructions about how to proceed with our work. In times of severe difficulties, he inspired us well and helped us to overcome the situation.Last but not least, we are thankful to the faculties, seniors, friends and our beloved family who have motivated and inspired us throughout this journey. We should also appreciate all sorts of knowledge we could acquire from various resources from the internet from the work of fellow scholars and researchers.ii | P a g e Abstract Advancements in computing speed and power have made revolutionary changes in medical science practices and this is no different for cardiology. Such advancements in computer sciences have made the existing medical tests of heart into being. These tests are: ECG, CTA, & Echocardiogram. CTA (Computed Tomography Angiography) is a widely used imaging technique to visualize arterial and venous vessels throughout the body. In clinical practice, the analysis mainly relies on visual inspection or manual measurements by experienced cardiologists. The proposed method aims towards a full automation of the detection of coronary artery blockage through some image processing techniques so that the system does not have to rely on any human's inspection. The goal of the research is to implement the proposed image processing techniques so that the system can detect the narrowing area of the wall of coronary arteries due to the condensation of different artery blocking agents. This detection is crucial for further analysis of the heart. The research suggests that the system will require a 64-slice CTA image as input. After the acquisition of the desired input image, it will go through several steps to determine the region of interest. This research proposes a two stage approach that includes the pre-processing stage and decision stage. The pre-processing stage involves common image processing strategies while the decision stage involves the extraction and calculation of two feature ratios to finally determine the intended result. In order to get more insights of the subject of these examinations, this research has proposed the use of an algorithm to create a 3-D model. Moreover, the system to work more precisely and effectively, use of several techniques have been suggested including parallel processing with shared memory allocation between the CPU and the GPU. Using the parallel processing technique not only makes the whole process at least 7 times faster, but also helps several stages of the process work more effectively.iii | P a g e

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