Fuzzy Clustering for Image Segmentation Using Generic Shape Information

Ali, Mortuza; Karmakar, Gour; Dooley, Laurence S.

doi:10.22452/mjcs.vol21no2.5

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…Precision is a prognostic factor, while recall is a quantitative indicator. The highest precision produces more effective findings than unnecessary ones [31,32,33], while the highest recall delivers the majority of significant findings. The reason for the improvement of results counters the existing approach quality testing has been done at every stage of system development.…”

Section: Discussionmentioning

confidence: 99%

Prior Detection of Alzheimer’s Disease With the Aid of Mri Images and Deep Neural Networks

Karthik

Nandihal²,

Seemanthini³

et al. 2022

MJCS

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Alzheimer's disease is a degenerative disease in which brain cells die and deteriorate. It is the most prevalent reason for dementia, which is defined as a progressive decrease in thinking, conduct, and social skills that impairs a person's capacity to operate independently. Although it is fatal the early diagnosis of Alzheimer's can be extremely helpful. Our main aim is to help with the diagnosis of this disease in its early stages using the VGG16 classifier which is a convolutional neural network (CNN) that is 16 layers deep. The dataset consists of MRI images of the brain. Data augmentation is done to significantly increase the diversity of data available and Data pre-processing helps to enhance the overall truthfulness of the proposed approach.

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Section: Discussionmentioning

confidence: 99%

Prior Detection of Alzheimer’s Disease With the Aid of Mri Images and Deep Neural Networks

Karthik

Nandihal²,

Seemanthini³

et al. 2022

MJCS

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“…In [10] the author has presented a technique of image segmentation that is known as shape-based segmentation of the image. This segmentation is also known as fuzzy clustering for image segmentation using generic shape information.…”

Section: Fig 2-image Segmentation Techniquementioning

confidence: 99%

Techniques for Image Segmentation: A Critical Review

Mishra¹,

Misra²

2021

IJRAT

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In today’s world there is requirement of some techniques or methods that will be helpful for retrieval of the information from the images. Information those are important for finding solution to the problems in the present time are needed. In this review we will study the processing involved in the digitalization of the image. The set or proper array of the pixels that is also called as picture element is known as image. The positioning of these pixels is in matrix which is formed in columns and rows. The image undergoes the process of digitalization by which a digital image is formed. This process of digitalization is called digital image processing of the image (D.I.P). Electronic devices as such computers are used for the processing of the image into digital image. There are various techniques that are used for image segmentation process. In this review we will also try to understand the involvement of data mining for the extraction of the information from the image. The process of the identifying patterns in the large stored data with the help of statistic and mathematical algorithms is data mining. The pixel wise classification of the image segmentation uses data mining technique.

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Fuzzy Clustering for Image Segmentation Using Generic Shape Information

Abstract: ABSTRACT

Cited by 2 publications

References 19 publications

Prior Detection of Alzheimer’s Disease With the Aid of Mri Images and Deep Neural Networks

Prior Detection of Alzheimer’s Disease With the Aid of Mri Images and Deep Neural Networks

Techniques for Image Segmentation: A Critical Review

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