A comprehensive review on medical image processing and its application for the automatic detection of tumor in human brain

Abstract

In Medical Image Processing (MIP), different types of medical images suffer with low contrast and noise. Enhancing
contrast, removing noise to increase quality of an image using image enhancement is essential. Image Segmentation
methods used for medical images for partitioning of an image into multiple segments. Medical Image Processing uses MR
images and Computer to diagnose different tumors and various types of diseases. Medical imaging is used to obtain the
physical information about the biological human body. In Medical field, the application of medical image processing is a
crucial task and an important vision application because some tumors are brain cancers. Brain tumor is growth of unhealthy
or abnormal cells and multiplies uncontrollably in brain which increases intracranial pressure and takes up space within the
skull and results as different types of tumors. Tumor in human brain interferes with normal brain activity and is a life
threatening disease which causes problems such as talking, understanding, speech learning, hearing and loss in memory.
An efficient brain tumor detection method consists of three important stages such as enhancement, segmentation and
classification. One of the most important techniques for detecting tumors is Magnetic Resonance Imaging (MRI) which
produces high quality of images of human soft tissues that helps in brain tumor diagnosis. Detecting location of the tumor,
tumor detection algorithms are used and to detect brain tumor image, segmentation techniques are used. Classification is
used to differentiate between patient normal and abnormalities or tumor. So, for the medical analysis and interpretation,
automatic detection and classification of tumors is important using MR images. In this paper, we are presented a review on
MIP, Medical Imaging along its application methodology to detect tumors.