Medical image processing schemes for cancer detection: A survey

In this paper, the survey has been proposed on “Medical Image processing schemes for cancer detection”. The various intelligent schemes available in the literature for cancer detections have been discussed. This paper provides details of different techniques that reveal how hybrid intelligent approaches are applied to different categories of cancer detections and treatments. The three major categories of cancer problems such as breast, liver and brain tumor using cancer data bases are clearly discussed. The methods and algorithms used for detecting cancers are FPGA(Field Programmable Gate Array) based 3-D Ultrasound Computer Tomography(3D-USCT) with image reconstruction algorithms, a resistively loaded wire bowtie antenna using genetic algorithm approach, ⁽¹¹¹⁾ In-pentetreotide Single-photon emission computed tomography(SPECT) based on Monte Carlo simulation and CA (Cellular Automata) Based Segmentation method. By reviewing all the methods available in the literature, it is found that each method has its own merits and demerits. This paper illustrates overview of various states of methods available in the cancer detection and comparison analysis of each method is discussed.