Classification and characterization of brain tumor MRI by using gray scaled segmentation and DNN
Tahir, Muhammad Naeem (2018)
Tahir, Muhammad Naeem
Tampereen ammattikorkeakoulu
2018
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2018062914285
https://urn.fi/URN:NBN:fi:amk-2018062914285
Tiivistelmä
Many efforts have been made for image segmentation and classification. Different techniques have been adopted for this purpose. Image segmentation is very valuable especially in biomedical field for diagnosing disease. Magnetic resonance imaging (MRI) is playing very important role in the research of neuroscience for studying brain images. This study of brain MR Images is helpful in brain tumor diagnosis process. Features will be extracted (on the bases of tumor region, exture, color, location and edge) and selected from the segmented images and then classified by using the classification techniques to diagnose whether the patient is normal (having no tumor) or abnormal (having tumor).Implementation of combination of techniques will increase the accuracy of results. In this thesis an effort will make to list and cover previous work of different researchers to improve the accuracy of diagnosis process.