Tumor detection using threshold operation in MRI brain images

Natarajan, Premkumar; Nallaperumal, Krishnan; Kenkre, Natasha Sandeep; Nancy, S. Gilbert; Singh, Bhuvanesh Pratap

doi:10.1109/iccic.2012.6510299

Cited by 92 publications

(39 citation statements)

References 2 publications

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“…It is based on threshold value or also called as clip-level value. In thresholding, morphological operations are essentially based on some assumptions regarding the dimensions and form of the brain tumor [1].…”

Section: Methods Of Segmentationmentioning

confidence: 99%

Brain tumor detection in magnetic resonance images

2017

IJLTET

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Section: Methods Of Segmentationmentioning

confidence: 99%

Brain tumor detection in magnetic resonance images

2017

IJLTET

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“…Magnetic resonance imaging (MRI) is a progressed diagnostic tool that helps diagnostics to picture anatomical subtle elements more plainly and so prevalent in identifying variations from the norm in the soft tissues of the brain. Therefore Segmentation techniques have been used for this purpose which is normally a long and decisive process commonly used from long time [7].This research will presents the comparison between previous method (PORTR) and proposed method (BBNC) to extract the tumor region from the medical images, and also will presents the 3-D view of extracted region from the medical images. There are various image segmentation procedures and they are discussed below:…”

Section: Introductionmentioning

confidence: 99%

Implementation of Biography Based Neural Clustering (BBNC) with Genetic Processing for Tumor Detection from Medical Images

Kaur¹,

Kaur²

2016

J Appl Bioinform Comput Biol

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Abstract. Segmentation is a best method to divide the required region from the medical images. This research is based on segmentation of medical images (MRI, CT scans) based on the previous method known as pre-operative and post-recurrence tumor registration (PORTR) and proposed method biography based neural clustering (BBNC) with genetic processing for tumor segmentation. By using the new technique the extracted part can be view in 3D model and also can get the actual segmented tumor region. This new method will be helpful for diagnostics to find the tumor area as well as pixel difference in segmented part to define the tumor area accurately. While in the previous approach all the parameters have been used likewise, in which the registration method is used to transform the different sets of data into one coordinate system for segmentation of medical images. Registration basically is used to improve the signals to reduce the noise from the images. These techniques are better to find the tumor area from the MRI and CT scans, but after comparing them better results have been obtained in proposed technique. The proposed technique (BBNC) reduces the extracted region again into required and actual region of tumor with accuracy of area, time and pixel difference.

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“…Multi-modular MR pictures with virtual tumor have been utilized as the ground truth for direction and defense of the acknowledgment method. [12] has concentrated that the Medical Image Processing is an intricate and testing field these days. Handling of MRI pictures is one of the parts of this field.…”

Section: Related Workmentioning

confidence: 99%

Enhanced Feature Extraction for Tumor Detection by using Decision based Joint Trilateral Filter

Pathania¹,

Kaur²

2017

IJERT

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Abstract-The brain tumor distinguishing proof is an indispensable utilization of restorative picture dealing with. The written work consider has shown that most by far of systems which are in presence has ignored the low institutionalized pictures like pictures with uproar or awful brightness. This examination works proposed another choice based joint trilateral filter and by utilizing this filter we got more effective and enhanced outcomes as correlation with the current strategies. By utilizing this procedure there will be less impact of clamor and the picture will be all the more clear as contrast with past techniques. The inspiration driving the proposed approach is simple and effective.

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Tumor detection using threshold operation in MRI brain images

Cited by 92 publications

References 2 publications

Brain tumor detection in magnetic resonance images

Brain tumor detection in magnetic resonance images

Implementation of Biography Based Neural Clustering (BBNC) with Genetic Processing for Tumor Detection from Medical Images

Enhanced Feature Extraction for Tumor Detection by using Decision based Joint Trilateral Filter

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