The Computed Tomography (CT) Scan Image Is The Most Reliable Method And Mostly Used In Radiotherapy As It Is Of Low Cost Yet Efficient Compared To The Magnetic Resonance Imaging (MRI) Scan. For Brain CT Scan Application Conversion Of Medical Images And Segmentation Techniques Are Essential. U-net Is A Neural Network Architecture Designed Primarily For Image Segmentation. These Traits Provide U-net With A High Utility Within The Medical Imaging Community And Have Resulted In Extensive Adoption Of U-net As The Primary Tool For Segmentation Tasks In Medical Imaging. The Success Of U-net Is Evident In Its Widespread Use In Nearly All Major Image Modalities, From CT Scans And MRI To X-rays And Microscopy. Given That U-net’s Potential Is Still Increasing, This Narrative Literature Review Examines The Numerous Developments And Breakthroughs In The U-net Architecture And Provides Observations On Recent Trends.
