DODOR: Dual Optimization for Detection of Oncological Region in radiological image

A precise diagnosis plays a very critical role in saving the life of a patient suffering from oncological diseases. For more than a decade, medical image processing has played a contributory role in detection of image region suspected for cancer, but till date none of discussed paper have ever made it to real-medical applications owing to various unsolved problems. The paper introduces a technique called as DODOR i.e. Dual Optimization for Detection Oncological Regions, where the input image is subjected to two levels of optimization viz. local and global level. The globally optimized signal is again subjected to another novel technique that performs further exhaustive search for elite regions inflicted with cancer. DODOR was evaluated on multiple database of oncology and was found to provide faster processing as well as lesser extent of false positive in contrast to one of the most significant study in this field.