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Convolutional neural networks for medical imaging diagnosis of osteosarcoma

Grant number: 20/01023-8
Support Opportunities: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 Investigator:Renato Tinós
Grantee:Larissa Yoshie Asito
Host Institution: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil


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)

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