A Review On Automatic Detection of Brain Tumor Using Computer Aided Diagnosis System Through MRI
Journal Title: EAI Endorsed Transactions on Energy Web - Year 2018, Vol 5, Issue 20
Abstract
In diagnosing brain tumor using Magnetic Resonance Imaging (MRI) plays a major role in complicated stages. To extract the images, it uses a kind of nuclear magnetic resonance technique. To identify the exact region where the tumor is present is the most important task in the segmentation process. The most challenging and complicated medical image processing technique Brain image segmentation. The researchers are working towards to develop effective procedure for segmenting MRI images. In this research article Pre-processing, Enhancement and Segmentation process are deeply surveyed.
Authors and Affiliations
Meera R, Dr. Anandhan, P
Sizing, modelling and simulation for Hybrid Central PV/wind turbine/diesel generator for feeding rural village in South Algeria
In this study, a hybrid system has been modulate and simulated, this system is composed with three generators, two on renewable energy (solar and wind power) and one on combustible energy (diesel generator). This central...
Low Energy Clustering in BAN Based on Fuzzy Simulated Evolutionary Computation
A low energy clustering method of body area networks based on fuzzy simulated evolutionary computation is proposed in this paper. To reduce communication energy consumption, we also designed a fuzzy controller to dynamic...
Simplifying the in-vehicle connectivity for ITS applications
In-vehicle connectivity has experienced a big expansion in recent years; car manufacturers are very active in this sense, and are proposing OBU oriented solutions. This effort is justified by the user demands for always-...
Welcome message from the Editors‐in‐Chief
Welcome to the inaugural edition of the EAI Endorsed Transactions on Energy Web Transactions! This journal is positioned at the forefront of the efforts related to the new generation of energy production and distribut...
Sensor-Based Activity Recognition with Dynamically Added Context
An activity recognition system essentially processes raw sensor data and maps them into latent activity classes. Most of the previous systems are built with supervised learning techniques and pre-defined data sources, an...