Abstract
A tumor also known as neoplasm is a growth in the abnormal tissue which can be differentiated from the surrounding tissue by its structure. A tumor may lead to cancer, which is a major leading cause of death and responsible for around 13% of all deaths world-wide. Cancer incidence rate is growing at an alarming rate in the world. Great knowledge and experience on radiology are required for accurate tumor detection in medical imaging. Automation of tumor detection is required because there might be a shortage of skilled radiologists at a time of great need. We propose an automatic brain tumor detection and localization framework that can detect and localize brain tumor in magnetic resonance imaging. The proposed brain tumor detection and localization framework comprises five steps: image acquisition, pre-processing, edge detection, modified histogram clustering and morphological operations. After morphological operations, tumors appear as pure white color on pure black backgrounds. We used 50 neuroimages to optimize our system and 100 out-of-sample neuroimages to test our system. The proposed tumor detection and localization system was found to be able to accurately detect and localize brain tumor in magnetic resonance imaging. The preliminary results demonstrate how a simple machine learning classifier with a set of simple image-based features can result in high classification accuracy. The preliminary results also demonstrate the efficacy and efficiency of our five-step brain tumor detection and localization approach and motivate us to extend this framework to detect and localize a variety of other types of tumors in other types of medical imagery.
Highlights
Based on statistics, tumors are the second cause of cancer-related deaths in children whose are under the age of 20 and in males whose age 20 to 39 [1,2,3,4,5,27]
This disease is the fifth leading cause of cancer-related deaths in females ages 20-39. This facts increase the importance of the researches on the tumor detection and this will present the opportunity for doctors to help save lives by detecting the disease earlier and perform necessary actions
This paper provide a review of image-based tumor detection
Summary
Tumors are the second cause of cancer-related deaths in children (both males and females) whose are under the age of 20 and in males whose age 20 to 39 [1,2,3,4,5,27]. Varieties of image processing techniques are available to be applied on various imaging modalities for tumor detection that will detect certain features of the tumors such as the shape, border, calcification and texture. It is basically used to detect the differences in the body tissues which have a considerably better technique as compared to computed tomography [23]. This technique become a special technique especially for the brain tumor detection and cancer imaging [23]. The authors review imagebased tumor detection, commenting on techniques applied for color detection and shape detection They provide their insights and perspectives on future research directions in imagebased tumor detection
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