Hybrid Soft Computing Algorithms for the diagnosis of Cervical Cancer

In real world many problems could not be solved using conventional problem solving methods. So efficient problem solving methods are necessary. Soft Computing is such an efficient problem solving method. It provides effective solutions in various fields such as Engineering Patter Recognition and Medical Diagnosis than the traditional problem solving methods. The main objective of this book is to propose Hybrid Soft Computing algorithms for efficient classification of Cervical Pap smear images. Medical Images has significant role in the identification of a disease. Manual diagnosis of disease may lead to human errors and time consuming. Therefore Medical Image Processing is essential in the diagnosis of Cervical Cancer through Pap smear image. To overcome the limitation of manual Cervical Cancer diagnosis effective Computer Aided Diagnosis (CAD) is necessary. The key components of Soft Computing techniques such as Fuzzy Logic Genetic Algorithm and Meta-heuristic algorithms are experimented in this book.