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Classification of MRI images of Brain Tumor to help the medical doctors in analyzing and interpreting the MRI images. Due to the increased disease rates in humans, the need for an Automated Disease Diagnosis (ADD) systems is also raised. Most of the ADD systems are proposed to support the doctor during the screening and decision making process. This research aims at developing a Computer Aided Disease Diagnosis (CADD) scheme to categorize the brain tumor of 2D MRI slices into Glioblastoma/Glioma class with better accuracy. The idea is to develop a CADD system with Convolutional-Neural-Network (CNN) supported segmentation and classification.

License: MIT License

Jupyter Notebook 57.12% Python 0.29% HTML 42.59%

tumorclass.info's Introduction

Hi, I'm Lewi Uberg 👋

I'm a husband, father of three boys, a former design egineer, and a final year data science student, currently working as a full-stack developer at Puzzel in Arendal, Norway.

I’m currently learning C# and JavaScript.
I'm a huge fan of the combination of pyenv, poetry, and zsh-autoswitch-virtualenv when I work on a project. The more I can control from pyptoject.tomlin my project the better.
A portfolio of some of my projects are available at https://uberg.me/portfolio/
I regularly write articles on https://uberg.me/posts/
Fun fact: I love woodworking and like to spend my free time in my workshop.