A Computer-aided Framework for Detecting Osteosarcoma in Computed Tomography Scans

Maximo Rodriguez-Herrero; Dante D. Sanchez-Gallegos; Marco Antonio Núñez-Gaona; Heriberto Aguirre-Meneses; Luis Alberto Villalvazo Gutiérrez; Mario Ibrahin Gutiérrez Velasco; J. L. Gonzalez-Compean; Jesus Carretero

arXiv · 2603.13376

A Computer-aided Framework for Detecting Osteosarcoma in Computed Tomography Scans

Maximo Rodriguez-Herrero·Dante D. Sanchez-Gallegos·Marco Antonio Núñez-Gaona·Heriberto Aguirre-Meneses·Luis Alberto Villalvazo Gutiérrez·Mario Ibrahin Gutiérrez Velasco·J. L. Gonzalez-Compean·Jesus Carretero

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Abstract

Osteosarcoma is the most common primary bone cancer, mainly affecting the youngest and oldest populations. Its detection at early stages is crucial to reduce the probability of developing bone metastasis. In this context, accurate and fast diagnosis is essential to help physicians during the prognosis process. The research goal is to automate the diagnosis of osteosarcoma through a pipeline that includes the preprocessing, detection, postprocessing, and visualization of computed tomography (CT) scans. Thus, this paper presents a machine learning and visualization framework for classifying CT scans using different convolutional neural network (CNN) models. Preprocessing includes data augmentation and identification of the region of interest in scans. Post-processing includes data visualization to render a 3D bone model that highlights the affected area. An evaluation on 12 patients revealed the effectiveness of our framework, obtaining an area under the curve (AUC) of 94.8\% and a specificity of 94.6\%.

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Maximo Rodriguez-Herrero, Dante D. Sanchez-Gallegos, Marco Antonio Núñez-Gaona, Heriberto Aguirre-Meneses, Luis Alberto Villalvazo Gutiérrez, Mario Ibrahin Gutiérrez Velasco, J. L. Gonzalez-Compean, Jesus Carretero. 2026-03-10. A Computer-aided Framework for Detecting Osteosarcoma in Computed Tomography Scans. https://arxiv.org/abs/2603.13376

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