Nowadays by growing the number of available medical imaging data, there is a great demand towards computational systems for image processing which can help with the task of detection and diagnosis. Early detection of abnormalities using computational systems can help doctors to plan an effective treatment program for the patient. The main challenge of medical image processing is the automatic computerized detection of a region of interest. In recent years in order to improve the detection speed and increase the accuracy rate of ROI detection, different models based on the human vision system, have been introduced. In this paper, we have provided a brief description of recent works which mostly used visual models, in medical image processing and finally, a conclusion is drawn about open challenges and required research in this field.