Comparative analysis of image enhancement techniques for braintumor segmentation: contrast, histogram, and hybrid approaches
Shoffan Saifullah,
Andri Pranolo,
Rafał Dreżewski
Abstract:This study systematically investigates the impact of image enhancement techniques on Convolutional Neural Network (CNN)-based Brain Tumor Segmentation, focusing on Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), and their hybrid variations. Employing the U-Net architecture on a dataset of 3064 Brain MRI images, the research delves into preprocessing steps, including resizing and enhancement, to optimize segmentation accuracy. A detailed analysis of the CNN-based U-Net arc… Show more
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