An enhance approach based on preprocessing strategies in lymphoma’s image classification

The body’s disease-fighting system is the lymphatic system. The lymph nodes, spleen, thymus gland and bone marrow are all part of it. Hodgkin’s lymphoma and Non-lymphoma Hodgkin’s are the two most common kinds of lymphoma. The treatment for this lymphoma is determined by its stage. Early detection aids in lowering and avoiding the death rate associated with lymphoma. There are numerous medical aids available to help people live longer and avoid death. There are a variety of medical diagnosis procedures used to provide treatment for this problem. The computing algorithm is crucial in assisting clinicians in the diagnosis of lymphoma. The goal of this study is to diagnose lymphoma illness using MRI data. In this work, pre-processing techniques are used to reduce noise in the Lymphoma image, allowing it to progress to the next phase. Filtering techniques are used to blur and smooth the image without affecting the pixel values during the preprocessing stage. R channel image and CLAHE are two filtering approaches. The distribution of pixels is determined using histogram distribution for both normal and processing before preprocessing the image and the results are compared after pre-processing. The outliers in the forms of lymphoma image have been removed in the comparison. The precision of the procedures utilised in this project has demonstrated their efficacy.