Comparative analysis of automated bone age assessment techniques

Mei Silviana Saputri, Ari Wibisono, Petrus Mursanto, Joachim Rachmad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, automated systems have been implemented in several medical application tasks. For instance, computerized assessment of bone age which utilized by radiologist and pediatrician. This tool is beneficial for monitoring growth condition in children. However, considering the right technique for constructing this computerized bone evaluation is crucial, specifically when enormous data used. In this study, 9 GB X-ray dataset with varied specifications is examined. To address the challenge, we adopt and compare deep learning with several machine learning techniques. ResNet50 which categorized as a deep learning technique is implemented in this study. In contrast, machine learning technique utilizes two keypoints features: Bag of Scale Invariant Feature Transform (SIFT) and Bag of Speeded Up Robust Features (SURF). Bone age is predicted based on those extracted features by several machine learning regression techniques, including Multilayer Perceptron Regressor, Support Vector Regressor, Random Forest Regressor, and XGBoost Regressor. Both techniques are compared quantitatively using three different measurements: Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and Symmetric Mean Absolute Percentage Error (SMAPE). Experiment results indicate that ResNet50 outperforms overall machine learning techniques. ResNet50 achieves 13.58 months of MAE, 17.14 months of RMSE and 16.81% of SMAPE.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3567-3572
Number of pages6
ISBN (Electronic)9781728145693
DOIs
Publication statusPublished - Oct 2019
Event2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy
Duration: 6 Oct 20199 Oct 2019

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2019-October
ISSN (Print)1062-922X

Conference

Conference2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
CountryItaly
CityBari
Period6/10/199/10/19

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  • Cite this

    Saputri, M. S., Wibisono, A., Mursanto, P., & Rachmad, J. (2019). Comparative analysis of automated bone age assessment techniques. In 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 (pp. 3567-3572). [8914274] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 2019-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2019.8914274