Effective Tumor Diagnosis based on Shape and Size of Tumor

The key aspects of cancer diagnosis include accurate detection of tumor size and shape, as well as efficient classification. Given study provides a brief overview of the recent developments in tumor classification approaches, tumor shape and size detection techniques. In this study, a tumor mask was imposed on the original medical image(s) using a logical AND operator. It also highlights the value of automated tumor size evaluation, which is crucial for classification, prediction, and future treatment. Further, it explores how to quantify tumor size more precisely and consistently using computer-aided methods (machine learning, deep learning, and image analysis). The aim of this study is to generate imposed images for future classification by fusing the tumor mask with image pixels. Then, the imposed images were classified into three categories namely benign, malignant, and malignant metastasis for effective tumor diagnosis. It will improve various aspects of tumor segmentation such as varied size and shape.