Advances and Challenges of Machine Learning in Brain Medical Imaging Data Analysis

Yinuo Zhang

2024

Abstract

In recent years, machine learning has become a critical method for medical imaging data analysis and has solved many problems in medical imaging. This study focuses on brain medical imaging data analysis, and summarizes the advances and challenges of machine learning in this field. The methods range from traditional machine learning models to emerging machine learning models. These approaches have been improved and solved many problems, such as image quality problem, generalization problem and so on. However, there are still many challenges for machine learning in the field of brain medical imaging, including data annotation and model training problem, non-interpretability of the model and Cross-domain and cross-site data integration problem. These challenges not only affect the depth of research, but also hinder the clinical translation of new technologies. Therefore, how to overcome these obstacles has become the key to promote the further development of this field. This study also proposes some possible solutions to these challenges that could be further explored in the future.

Paper Citation

in Harvard Style

Zhang Y. (2024). Advances and Challenges of Machine Learning in Brain Medical Imaging Data Analysis. In Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-754-2, SciTePress, pages 483-487. DOI: 10.5220/0013526400004619

in Bibtex Style

@conference{daml24,
author={Yinuo Zhang},
title={Advances and Challenges of Machine Learning in Brain Medical Imaging Data Analysis},
booktitle={Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2024},
pages={483-487},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013526400004619},
isbn={978-989-758-754-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Advances and Challenges of Machine Learning in Brain Medical Imaging Data Analysis
SN - 978-989-758-754-2
AU - Zhang Y.
PY - 2024
SP - 483
EP - 487
DO - 10.5220/0013526400004619
PB - SciTePress