Lymphatic Cancer Detection Using Machine Learning

Abstract

In Recent Days, Lymphatic Cancer Is Seen As One Of The Most Hazardous Form Of The Cancers Found In Humans. Lymphatic Cancer Is Found In Various Types In Lymph Nodes Among Which Is The Most Unpredictable. The Detection Of Cancer In Early Stage Can Be Helpful To Cure It. Computer Vision  Plays An Important Role In Medical Image Diagnosis And It Has Been Proved By Many Existing Systems. In This Project, We Present A Computer Aided Method For The Detection Of  Lymphatic Cancer Using Image Processing Tools. The Input To The System Is Lymphatic Lesion Image And Then By Applying Novel Image Processing Techniques, It Analyses To Conclude About The Presence Of  Lymphatic Cancer. The Lesion Image Analysis Tools Checks For The Various Parameters Like Asymmetry, Border, Colour, Diameter,(Abcd) Etc. By Texture, Size And Structure Analysis For Image Segmentation And Feature Stages.  The Extracted Feature Parameters Are Used To Classify The Image As Normal Lymphatic And  Cancer Lesion. Early Detection Of Lymphatic Cancers Can Change The Survival Rate Of The Most Cancers Patient. Overall 5-Year Survival Rate For Cancer Patient Increases From 87%To 91% If Cancer Is Detected In Time. In This Paper We Are Using The Combination Of Image Processing With Machine Learning And We Are Aiming To Get The More Accurate Results By Using Raspberry Pi With Machine Learning