Deep Learning Approaches to Osteosarcoma Diagnosis and Classification: A Comparative Methodological Approach.

ABSTRACT:

Background

Osteosarcoma is the most common primary malignancy of the bone, being most prevalent in childhood and adolescence. Despite recent progress in diagnostic methods, histopathology remains the gold standard for disease staging and therapy decisions. Machine learning and deep learning methods have shown potential for evaluating and classifying histopathological cross-sections.

Methods

This study used publicly available images of osteosarcoma cross-sections to analyze and compare the performance of state-of-the-art deep neural networks for histopathological evaluation of osteosarcomas.

Results

The classification performance did not necessarily improve when using larger networks on our dataset. In fact, the smallest network combined with the smallest image input s

SUBMITTER: Vezakis IA 

PROVIDER: S-EPMC10136449 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature