Abstract
Abstract: The research concentrates on enhancing the precise identification and localization of diseases within medical images, a pivotal component of medical imaging analysis crucial for diagnoses and treatment planning. Employing the U-Net architecture, renowned for its effectiveness in biomedical image segmentation, the study targets the detection of brain tumors and skin lesions in MRI or CT scans. Remarkably, the proposed method not only identifies diseases but also provides intricate details regarding their dimensions and spatial arrangement. Extensive experimental validation showcases the method's superiority over existing approaches, underscoring its potential for holistic learning in medical image analysis.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal for Research in Applied Science and Engineering Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
