A new approach for enhancing the quality of medical images using adaptive genetic algorithm two fold hybrid binary particle swarm optimization and binary flower pollination algorithm

Abstract

In health care sectors to improve medical diagnosis system needs assistant as secondary opinion for medical practitioners so it is evident that there is a need for Medical Decisiveness Determine System and the system MDDS should be able to diagnosis abnormalities in medical imaging Medical images usually encounter with abnormal brightness or poor contrast that arises from various factors like inexperience during image acquisition and imaging device deficiency The high or low illuminance intensity during the capturing scenes leads to improper or reduced contrast quality Apart from the degradation of visual quality low contrast level in an image affects the digital image applications that include analysis of image digital printing and object recognition etc Hence it is very necessary to improve the contrast nature of a distorted reference image The processed computer based output can be used as secondary opinion for health care professionals to diagnose the patient diseases These techniques are expected to be more accurate compared to original image The MDDS has been developed to identify various diseases like Breast cancer Head and Neck cancer Fetal Brain Cancer from Magnetic Resonance images and presented in this thesis The system is expected to be the secondary opinion for efficient diagnostic decision making process by improving the contrast level of the medical image newline