A Survey on Medical Image Segmentation Methods with Different Modalitites

Sumithra, M. G.; Malathi, S.

doi:10.17577/ijertcon030

Cited by 4 publications

(3 citation statements)

References 75 publications

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“…we proposed a Deep Learning (DL) based brain tumor prediction method to prevent disease by cultivating. The DL method used in the study is the Convolution Neural Network (CNN) [10]. It is predicted that the success of the obtained results will increase if theCNN method is supported by adding extra feature [8]extraction methods and classify successfully brain tumor.…”

Section: Introductionmentioning

confidence: 99%

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MRI Image Classification of Brain Tumor Using Deep Neural Network and Deployment using Web Framework

Sumithra¹,

Shruthi²,

SmithiRam³

et al. 2021

Advances in Parallel Computing

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A brain tumor is a mass or growth of abnormal cells in our brain. Many different types of brain tumors exist. Some brain tumors are noncancerous (benign), and some brain tumors are cancerous (malignant). Brain tumors can begin in your brain (primary brain tumors), or cancer can begin in other parts of your body and spread to your brain (secondary, or metastatic, brain tumors). Brain tumor treatment options depend on the type of brain tumor you have, as well as its size and location. The classification of brain tumors is performed by biopsy, which is not usually conducted before definitive brain surgery. The improvement of technology and machine learning can help radiologists in tumor diagnostics without invasive measures. A machine-learning algorithm that has achieved substantial results in image classification is the convolution neural network (CNN). It is predicted that the success of the obtained results will increase if the CNN method is supported by adding extra feature extraction methods and classify successfully brain tumor normal and abnormal image.

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Section: Introductionmentioning

confidence: 99%

“…It is done in Django framework with slight 3 database. The user uploads the image in .h5 format (hierarchical data format [9]) which is the supported format in the python framework.…”

Section: Introductionmentioning

confidence: 99%

MRI Image Classification of Brain Tumor Using Deep Neural Network and Deployment using Web Framework

Sumithra¹,

Shruthi²,

SmithiRam³

et al. 2021

Advances in Parallel Computing

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“…The radio waves manipulate the position of the atoms which is send to the system for producing images. It provides a clear vision of the brain in comparison to CT, X-ray or ultrasound [7]. CT scans are widely used as they are less expensive.…”

Section: Introductionmentioning

confidence: 99%

A Review on Stroke Lesion Analysis in MRI Datasets

Irish¹,

J²

2020

Intelligent Systems and Computer Technology

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Stroke is one of the major causes of disability in the world. The various disabilities due to stroke includes intellectual functioning damage locomotory dysfunction, visual and hearing impairment, disfigurement etc., This occurs due to occlusion or inhibition of blood supply to the brain which is known as Ischemic stroke, whereas rupturing of blood vessels to the brain causes hemorrhagic stroke. Imaging techniques such as CT and MRI have played a huge role in the visualization of stroke lesions. Segmentation of the salvageable tissue and its outcome of how it affects a person’s lifestyle is the key focus of research as automated model is highly recommended to reduce the time and increase the accuracy in the prediction of stroke lesion in comparison to manual intervention.

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