An efficient method for identification of anomalies in brain MR images

Bhima, K.; Jagan, A

doi:10.1109/iconsip.2016.7857473

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Cited by 2 publications

(2 citation statements)

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“…Early X-ray systems used a contrast agent and planar projections to generate different views which, after interpretation by a trained expert, produced an estimation of the extent of lumen narrowing. More recent techniques use 3D CT (CTA) [14] but still require the injection of a contrast agent opaque to X-ray. One advantage of CTA is the clear visualization of calcifications and ossifications, almost always associated to advanced atherosclerotic lesions [15].…”

Section: Description Of Mri Imagesmentioning

confidence: 99%

Correction of MRI Image Intenseness by Minimization of Energy Approach

Ali¹,

Kumar²

2017

IJSIP

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Section: Description Of Mri Imagesmentioning

confidence: 99%

Correction of MRI Image Intenseness by Minimization of Energy Approach

Ali¹,

Kumar²

2017

IJSIP

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“…The existing techniques used for tumour detection uses various methods using MRI images. Texture based feature analysis [8] and water shed algorithm [9] is mainly used for brain tumour detection. Expectation maximization method [10] is used for brain anomalies detection based on bilateral filter [10].…”

Section: Introductionmentioning

confidence: 99%

A symmetry based anomaly detection in brain using cellular automata for computer aided diagnosis

Nisha

Jeganathan

2018

IJEECS

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Computer aided diagnosis (CAD) is an advancing technology in medical imaging. CAD acts as an additional computing power for doctors to interpret the medical images which leads to a more accurate diagnosis of the disease.CAD system increases the chances of detection of brain lesions by assisting the physicians in decreasing the observational oversight in the early stage of diseases.This paper focuses on the development of a cellular automata based model to find the anomaly prone areas in human brains.Because of the bilateral symmetric nature of human brain, a symmetry based cellular automata model is proposed.An algorithm is designed based on the proposed model to detect the anomaly prone areas in brain images. The proposed model can be a standalone model or it can be incorporated to a sophisticated computer aided diagnosis system. By incorporating asymmetry information into a computer aided diagnosis system, enhances its performance in identifying the anomalies exists in bilaterally symmetrical brain images.

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An efficient method for identification of anomalies in brain MR images

Cited by 2 publications

References 14 publications

Correction of MRI Image Intenseness by Minimization of Energy Approach

Correction of MRI Image Intenseness by Minimization of Energy Approach

A symmetry based anomaly detection in brain using cellular automata for computer aided diagnosis

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