The Advancements of Convolutional Neural Networks on Cerebral Hemorrhage Detection

Xiao Liu

2024

Abstract

Cerebral hemorrhage is a common and serious disorder that poses a serious threat to the health of the patient. Due to the shortcomings, such as the low efficiency of traditional cerebral hemorrhage detection, it is rather necessary to consider techniques combined with artificial intelligence to enhance the quality and speed of detection because of the intractability of the disease. In this paper, a method using convolutional neural networks (CNN) is considered, studied, and further discussed. Currently, deep-learning-based automated cerebral hemorrhage detection methods have gained widespread attention. These approaches have achieved rapid and accurate brain bleeding detection by analyzing head imaging data, such as computerized tomography (CT) images. Some professors adopted a special technique or structure, for example, the attention mechanism or hybrid CNN, to detect and classify the CT images, which has already gained wonderful achievements. The use of attention mechanisms or mixed CNN for brain hemorrhage testing contributes to improving the accuracy, adaptability, and efficiency of testing, which is one of the important directions of current research. However, in practical applications, some models have been poorly performed in dealing with specific types of brain bleed and have limited generalization capabilities. The focus in this field includes improving character representation, optimizing model structures, and solving data deviations to improve the generalizing capability and accuracy of models. In conclusion, this paper provides a good overview of cerebral hemorrhage detection.

Paper Citation

in Harvard Style

Liu X. (2024). The Advancements of Convolutional Neural Networks on Cerebral Hemorrhage Detection. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 306-310. DOI: 10.5220/0012937200004508

in Bibtex Style

@conference{emiti24,
author={Xiao Liu},
title={The Advancements of Convolutional Neural Networks on Cerebral Hemorrhage Detection},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={306-310},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012937200004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - The Advancements of Convolutional Neural Networks on Cerebral Hemorrhage Detection
SN - 978-989-758-713-9
AU - Liu X.
PY - 2024
SP - 306
EP - 310
DO - 10.5220/0012937200004508
PB - SciTePress