Texture, Morphology, and Statistical Analysis to Differentiate Primary Brain Tumors on Two-Dimensional Magnetic Resonance Imaging Scans Using Artificial Intelligence Techniques.

ABSTRACT:

Objective

A primary brain tumor starts to grow from brain cells, and it occurs as a result of errors in the DNA of normal cells. Therefore, this study was carried out to analyze the two-dimensional (2D) texture, morphology, and statistical features of brain tumors and to perform a classification using artificial intelligence (AI) techniques.

Methods

AI techniques can help radiologists to diagnose primary brain tumors without using any invasive measurement techniques. In this paper, we focused on deep learning (DL) and machine learning (ML) techniques for texture, morphological, and statistical feature classification of three tumor types (namely, glioma, meningioma, and pituitary). T1-weighted magnetic resonance imaging (MRI) 2D scans were used for analysis and classification

SUBMITTER: Bhattacharjee S 

PROVIDER: S-EPMC8850171 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature