An Intelligent framework for Detection and Classification of MRI Brain Tumour using SIFT-SURF Features and K-nearest Neighbour Approach

2020 ◽  
Vol 7 (10) ◽  
Keyword(s):  
Brain Tumour ◽  
Nearest Neighbour ◽  
Mri Brain ◽  
Surf Features

Detection and Classification of MRI Brain Tumour Using GLCM and Enhanced K-NN

2021 ◽  
Author(s):  
Shenbagarajan Anantharajan ◽  
Shenbagalakshmi Gunasekaran
Keyword(s):  
Brain Tumour ◽  
Mri Brain

Automated System Design for Classification of Chronic Lung Viruses using Non-Linear Dynamic System Features and K-Nearest Neighbour

2021 ◽  
Author(s):  
Misha Urooj Khan ◽  
Ayesha Farman ◽  
Asad Ur Rehman ◽  
Nida Israr ◽  
Muhammad Zulqarnain Haider Ali ◽  
...  
Keyword(s):  
Dynamic System ◽  
System Design ◽  
Linear Dynamic System ◽  
Automated System ◽  
Nearest Neighbour ◽  
Linear Dynamic ◽  
Non Linear

scholarly journals An Improved Dual Clustering Method for Classification of Microarray Image Segementation

2019 ◽  
Vol 8 (4) ◽  
pp. 2514-2519
Keyword(s):  
Support Vector Machine ◽  
Ct Scanning ◽  
Support Vector ◽  
Nearest Neighbour ◽  
Resonance Imaging ◽  
Computerised Tomography ◽  
Medical Field ◽  
Microarray Image ◽  
Image Segementation

Microarray is a fast and rapid growing technology which plays dynamic role in the medical field. It is an advanced than MRI (Magnetic Resonance Imaging) and CT scanning (Computerised Tomography). The purpose of this work is to make fine perfection against the gene expression. In this study the two clustering are used which fuzzy c means and k means and also it classifies with better results. The microarray data base indicates the classification in support vector machine. Segmentation is most important step in microarray image. The classification in support vector machine is compared with other two classifiers which means the k nearest neighbour and with the Bayes classifiers.

Characteristics of Brain Tumour-Associated Headache

Cephalalgia ◽  
2007 ◽  
Vol 27 (8) ◽  
pp. 904-911 ◽  
Author(s):  
CJ Schankin ◽  
U Ferrari ◽  
VM Reinisch ◽  
T Birnbaum ◽  
R Goldbrunner ◽  
...  
Keyword(s):  
Brain Tumour ◽  
Univariate Analysis ◽  
Positive Family History ◽  
Primary Headache ◽  
Tension Type Headache ◽  
Moderate Intensity ◽  
Secondary Headache ◽  
History Of ◽  
Type Headache

Eighty-five brain tumour patients were examined for further characteristics of brain tumour-associated headache. The overall prevalence of headache in this population was 60%, but headache was the sole symptom in only 2%. Pain was generally dull, of moderate intensity, and not specifically localized. Nearly 40% met the criteria of tension-type headache. An alteration of the pain with the occurrence of the tumour was experienced by 82.5%, implying that the preexisting and the brain tumour headaches were different. The classic characteristics mentioned in the International Classification of Headache Disorders (worsening in the morning or during coughing) were not found; this might be explained by the patients not having elevated intracranial pressure. Univariate analysis revealed that a positive family history of headache and the presence of meningiomas are risk factors for tumour-associated headache, and the use of β-blockers is prophylactic. Pre-existing headache was the only risk factor according to logistic regression, suggesting that patients with pre-existing (primary) headache have a greater predisposition to develop secondary headache. Dull headache occurs significantly more often in patients with glioblastoma multiforme, and pulsating headache in patients with meningioma. In our study, only infratentorial tumours were associated with headache location, and predominantly with occipital but rarely frontal pain.

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