Detection of Brain Tumor using Image Processing Techniques

Abstract

Image processing in biomedical field is being increasingly used for the detection and diagnosis of various abnormalities in the body parts. The detection of brain tumours using image processing on MRI images is one such field where better results are obtained as comparative to CT-scan and x-ray. Prior detection of the brain tumour is desirable and possible with the help of machine learning and image processing techniques. These techniques detect even a small abnormality in the human brain following a four-stage process which includes pre-processing, segmentation, feature extraction and optimization. Different parameters such as accuracy, PSNR, MSE are calculated to find out the efficiency of process and to compare it with other methods. This paper reviews about various different approaches which are used to detect the brain tumor using image processing techniques.

Developing an Identification System for Different Types of Edible Mushrooms in Sri Lanka using Machine Learning and Image Processing

“…Research have state that the performance of Bayesian classifier is superior compared to the performance of decision tree and chosen neural network [9]. Naive bayes exhibits more accuracy than KNN when employed in image processing techniques to categorize mushrooms [10]. Artificial neural networks (ANN) are parallel computational models with highly linked adaptive processing units that can learn from experience as well as acquire new information.…”