3D Magnetic Resonance Image Segmentation Using HD Brain Extraction in 3D Slicer

Abstract

Applications of image processing in radiology and radiation are critical for the development of models, simulations, and computational tools. 3D Slicer is a widely used platform for processing, segmenting, visualizing, registering, and analyzing medical images, as well as for image-guided treatments. Image segmentation, which focuses on identifying specific regions in the image such as tumors or lesions, is one of the most common challenges in medical image processing. In this research work we have utilized 3D Slicer to implement simulation techniques and automation for imaging diagnostics, computation, and prediction. This paper expands on the HD Brain Extraction module in 3D Slicer to autonomously segment brain MRI images using artificial intelligence. To optimize the brain extraction process, various adjustable parameters including segmentation techniques, threshold values, and smoothing factors are fine-tuned. The brain is then extracted from MRI images for further analysis and visualization.