Medical Image Processing for Enhancing Brain Segmentation Images

Medical image processing has emerged as a crucial tool for enhancing the accuracy and efficiency of brain segmentation images. This paper explores various techniques employed in medical image processing to improve the quality of brain segmentation, which is vital for diagnosing and treating neurological conditions. The study focuses on methods such as manual, automatic, and semi-automatic segmentation, highlighting their applications, advantages, and limitations. A comprehensive literature review provides an overview of current advancements and challenges in the field. The methodology section details the data collection process, preprocessing steps, and the implementation of different segmentation algorithms. Quantitative and qualitative results demonstrate the effectiveness of these methods in achieving precise brain segmentation. The discussion compares the proposed techniques with existing methods, emphasizing the improvements and potential drawbacks. Finally, the paper concludes with a summary of findings and suggests directions for future research to further enhance brain image segmentation. The ongoing research and development efforts hold promise for even greater advancements, ultimately leading to better healthcare outcomes and a deeper understanding of brain structure and function.

کلیدواژه ها:

image processing ، brain segmentation ، image preprocessing ، manual segmentation