Convolutional neural networks for medical imaging diagnosis of osteosarcoma

• Grant number: 20/01023-8
• Support type: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): June 01, 2020
• Effective date (End): December 31, 2020
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal researcher: Renato Tinós
• Grantee: Larissa Yoshie Asito
• Home Institution: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

Osteosarcoma is the most common type of cancer in the bones. In this work, X-ray images will be classified using Machine Learning (ML) methods. The method should aid the detection of osteosarcoma at different levels of malignancy. Currently, there has been a great interest in using Convolutional Neural Networks for the classification of medical images. The main advantage of these neural networks is to automatically extract useful characteristics for classification without pre-processing the datasets. In this project, Convolutional Neural Networks will be used for the detection of Osteosarcoma. The neural network should classify the Osteosarcoma and identify regions affected by the tumor. (AU)