Voxel based lesion segmentation through SVM classifier for effective brain stroke detection

Lakshmi, R.; Babu, Melingi Sunil; Vijayalakshmi, V.

doi:10.1109/wispnet.2017.8299925

Cited by 5 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3) Author [3] In this paper , The categorization into ischemic stroke(AIS) and non-AIS phenotypes is done from the brain MRI radiology on the basis of performance of natural language processing (NLP) and evaluated Machine algorithm. [4] They presented their work on Otsu Thresholding based SVM classifier for the detection of ischemic strokes. To train the model, 2 distinct kinds of brain MRI pictures in JPEG format were utilised as the dataset.…”

Section: ) Authormentioning

confidence: 99%

Brain Stroke Prediction using Machine Learning

Deshpande,

Bahirat,

Dalvi

et al. 2023

IJRASET

View full text Add to dashboard Cite

A brain stroke, is a saviour disease in which a blood cot or bleeding occur in the brain during a stoke, which can result in long-term harm. This can affects person’s move, think, see, or communicate. The another medical name for the Brain Stroke is cerebrovascular or CVA is when The body part that the blood-starved brain cells regulate ceases to function. Brain Stroke is very critical situation as it directly leads to death or permanent disability. The stroke is classified into two areas ischemic stroke and Haemorrhagic. When blood clots re created in the brain and goes through the patient’s streamed lodge in the brain then there is the high chances of ischemic stroke occur. Homographic stroke is second type of stoke which occurs when there is leak of blood or ruptures in the artery in brain. In early stage if the treatment get started we can treat to the ischemic stroke efficiently. If a stroke is feared, or bystanders should call emergency medical services right away. Symptoms disappear as their own in a Ischemic stroke reminded by Transient Ischemic Attack (TIA). As per the research of World Health Organization the 2 nd leading cause of the death worldwide is Brain Stroke which is also responsible for the approximately 11% deaths. but can prevent up to 80% of stokes if they can be identified or predicted early stage stroke. Our ML model uses dataset to predict whether the person has any chances of getting stroke the parameters that are considered to predict stroke are gender, age, disease, smoking status, Cystatin-c , MMP10, Tau Our dataset focuses on major factors which has causes of brain stroke.

show abstract

Section: ) Authormentioning

confidence: 99%

Brain Stroke Prediction using Machine Learning

Deshpande,

Bahirat,

Dalvi

et al. 2023

IJRASET

View full text Add to dashboard Cite

show abstract

“…In the research conducted by R. Punitha Lakshmi et al [4], they put forward their work on SVM Classifier Based On Otsu Thresholding For Ischemic Stroke Detection. The dataset used in order to train the algorithms/models were a set of 32 different types of brain MRI images which were in JPEG format.…”

Section: Literature Surveymentioning

confidence: 99%

“…Thus, the maximum accuracy was given by SVM Classifier being 88% and Random Forest Classifier being at 81%. The paper concluded with the understanding of how maximum accurate segmentation of brain and brain lesions is achieved with the help of SVM Classifier based on Otsu Thresholding and the dataset with scattering lesion tissues can also help to improve further accuracy rates of this Classification [4].…”

Section: Literature Surveymentioning

confidence: 99%

An Analysis of Brain Stroke Prediction Using Machine Learning

Ponaganti

2020

TURCOMAT

View full text Add to dashboard Cite

A stroke, also known as a cerebrovascular accident or CVA, is when part of the brain loses its blood supply and the part of the body that the blood-deprived brain cells control stops working. This loss of blood supply can be ischemic because of lack of blood flow, or haemorrhagic because of bleeding into brain tissue. A stroke is a medical emergency because strokes can lead to death or permanent disability. There are opportunities to treat ischemic strokes, but that treatment needs to be started in the first few hours after the signs of a stroke begin. The patient, family, or bystanders should activate emergency medical services immediately should a stroke be suspected. A transient ischemic attack (TIA or mini stroke) describes an ischemic stroke that is short-lived where the symptoms resolve spontaneously. This situation also requires emergency assessment to try to minimize the risk of a future stroke. By definition, a stroke would be classified as TIA if all symptoms resolved within 24 hours. According to the World Health Organization (WHO) stroke is the 2nd leading cause of death globally, responsible to approximately 11% of total deaths. For survival prediction, our ML model uses dataset to predict whether a patient is likely to get stroke based on the input parameters like gender, age, various diseases, and smoking status. Unlike most of the datasets, our dataset focuses on attributes that would have a major risk factor of a Brain Stroke.

show abstract