MRI Sagittal Image Segmentation from Patients with Abdominal Aortic Aneurysms

Riminarsih, Desti; Karyati, Cut Maisyarah; Mutiara, Achmad Benny; Wahyudi, Bambang; Ernastuti, E.

doi:10.12928/telkomnika.v14i3.3520

Cited by 2 publications

(1 citation statement)

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“…It uses both the information of texture histogram and the color histogram for measuring the similarities of various regions and to guide the process region margining. The sagittal image segmentation to get aorta in a gray level image is discussed in [14]. It is a semi automatic segmentation process to segment the sagittal MRI image base that is connected to the labeling method components.…”

Section: Introductionmentioning

confidence: 99%

An Non Destructive Test for the Detection of Weld Defects Using Image Processing

Kalaiselvi¹,

D²

2018

IJEECS

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Welding is a fabrication of joining materials into one component. Defects are unavoidable during the welding process, and hence the inspection of welds is a most important task in many industries. In this work, a Computer Aided Detection (CAD) system is designed to detect weld defects based on image processing techniques. It is a non-destructive testing which uses X-ray images. The proposed system mainly consists of three stages; gradient image formation, filtration by Gaussian pyramidal filters algorithm and segmentation by Expectation and Maximization (EM) algorithm. In this study, GD X-ray weld image database is used to evaluate the proposed system. The performance analysis of the proposed system is done by measuring the sensitivity, specificity, and accuracy of the segmented image with the help of its corresponding ground truth images.

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Section: Introductionmentioning

confidence: 99%

An Non Destructive Test for the Detection of Weld Defects Using Image Processing

Kalaiselvi¹,

D²

2018

IJEECS

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Image Processing of Panoramic Dental X-Ray for Identifying Proximal Caries

et al. 2017

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This study aims to facilitate the identification of proximal caries in the Panoramic Dental X-Ray image. Twenty-seven X-Ray images of proximal caries were elaborated. The images in digital form were processed using Matlab and Multiple Morphological Gradients. The process produced sharper images and clarifies the edges of the objects in the images. This makes the characteristics of the proximal caries and the caries severity can be identified precisely.

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MRI Sagittal Image Segmentation from Patients with Abdominal Aortic Aneurysms

Abstract: Early detection in patients with

Cited by 2 publications

References 9 publications

An Non Destructive Test for the Detection of Weld Defects Using Image Processing

An Non Destructive Test for the Detection of Weld Defects Using Image Processing

Image Processing of Panoramic Dental X-Ray for Identifying Proximal Caries

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