Convolutional Neural Networks (CNNs)-Based for Medical Image Analysis

Leyan Li

2024

Abstract

This paper provides an exhaustive examination of convolutional neural networks (CNNs) in medical image processing, recognizing their pivotal role in healthcare diagnostics. As CNNs continue to evolve, they offer promising avenues for enhancing accuracy and efficiency in image analysis. The primary objective of this study is to scrutinize and assess the performance of both classic and contemporary CNN models across a spectrum of pathological datasets. The methodology entails a comprehensive analysis of various CNN architectures, ranging from well-established models to more advanced approaches. Emphasis is placed on their efficacy in disease classification and feature extraction tasks. Experiments conducted on datasets underscore the models' adeptness in handling intricate medical images. The findings indicate CNNs' superiority in feature extraction, the proficiency of Residual Network (ResNet) in managing depth and ensuring robust training, and Transformers' effectiveness in navigating high-dimensional data through their attention mechanisms. These insights hold profound implications for medical diagnostics, promising significant advancements in accuracy and timeliness of health interventions.

Paper Citation

in Harvard Style

Li L. (2024). Convolutional Neural Networks (CNNs)-Based for Medical Image Analysis. 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 546-552. DOI: 10.5220/0012958600004508

in Bibtex Style

@conference{emiti24,
author={Leyan Li},
title={Convolutional Neural Networks (CNNs)-Based for Medical Image Analysis},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={546-552},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012958600004508},
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 - Convolutional Neural Networks (CNNs)-Based for Medical Image Analysis
SN - 978-989-758-713-9
AU - Li L.
PY - 2024
SP - 546
EP - 552
DO - 10.5220/0012958600004508
PB - SciTePress