Deep Learning for Oral Cancer Detection: An Automated Analysis of Multimodal Medical Images

The book explores how deep learning (DL), a subset of AI, can revolutionize the way oral cancer is detected. The work uses both histopathological images (tissue samples under the microscope) and clinical photographic images (simple camera photos) to develop intelligent, automated systems that can spot signs of cancer early and accurately. This book offers a comprehensive, multi-pronged approach to oral cancer detection: It customizes DL models for histopathological image analysis, offering a robust alternative to manual biopsy grading. It pioneers the use of ordinary photographs for oral cancer screening, making early detection more affordable, accessible, and user-friendly. It introduces Genetic Algorithms (GAs) to optimize CNN performance, increasing model efficiency and reliability. Together, these contributions show deep learning can help shift oral cancer diagnosis from slow, expert-driven systems to quick, scalable, and consistent solutions.

Pagina's: 124, Paperback, LAP LAMBERT Academic Publishing