Identification of Brain Regions Most importantly for neurological research and their diagnosis, identification of brain regions needs to be quite accurate. The traditional methods suffer noise interference and therefore lack precise boundary detection. The present paper proposes a refined methodology for the detection of the boundary of brain regions using synergy of Total Variation (TV) Denoising enhanced with a dual optimization algorithm and advanced semantic segmentation techniques. Comparing evaluations are provided for the system on PSNR and MSE: the technique, besides showing excellent noise reduction, has its improvements substantial. Such capacity allows delineation to a great extent with a high degree of reproducibility and precision even in adverse imaging conditions. With the merits of both high accuracy and possibilities for efficiency of computation, the approach may revolutionize the techniques of brain mapping in academic and clinical applications.