相关实验视频

Updated: May 11, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

卷积神经网络在医疗图像中的应用:一个文献计量分析

Huixin Jia¹, Jiali Zhang¹, Kejun Ma²

¹School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China.

Quantitative imaging in medicine and surgery

|May 9, 2024

概括

这项文献计量研究分析了医学成像中的卷积神经网络 (CNN),揭示了关键趋势和挑战. 它强调了CNN研究的指数增长,重点关注特定的模型和疾病领域,如COVID-19和脑成像.

科学领域:

医疗成像医学成像
人工智能的人工智能
图书统计学图书统计学

背景情况:

卷积神经网络 (CNN) 在医疗成像中为医疗保健资源保护提供了显著的潜力.
挑战包括高数据注释成本,隐私问题,有限的模型解释性和大量的计算需求.
优化CNN集成对于提高诊断精度和效率至关重要.

研究的目的:

提供关于CNN在医学成像中的应用研究的综合图书统计概述.
分析出版趋势,识别有影响力的国家,机构和作者.
探索新兴主题和未来的研究方向,使用文献计量和主题建模技术.

主要方法:

在2013年至2023年期间发表的6310篇文章的图书统计分析.
进行了频率统计,集群分析和共同引用分析.
隐性迪里克莱特分配 (LDA) 用于主题建模和趋势分析.

主要成果:

美国在引用方面领先,而中国在出版物方面领先.
哈佛大学是最有影响力的机构;残余神经网络 (ResNet) 和U-Net是CNN的杰出模式.
COVID-19和与大脑相关的研究是焦点,计算机断层扫描 (CT) 成像主导着景观.

结论:

在过去的十年中,CNN在医学成像方面的研究经历了指数级增长.
在CNN发展的关键里程碑,从LeNet到AlexNet,都被强调.
未来的方向包括半监督,高效,值得信赖和联合学习的进步,解决持续存在的挑战.

关键词:

卷积神经网络 (CNN) 是一种神经网络.文献数量计学文献数量计学文献量计学隐藏的迪里克莱特分配主题建模 (LDA主题建模)医学图像医学图像医学图像一个里程碑式的里程碑.

更多相关视频

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

相关概念视频

Convolution: Math, Graphics, and Discrete Signals

Convolution: Math, Graphics, and Discrete Signals

In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...

Imaging Studies VII: Vascular Imaging

Imaging Studies VII: Vascular Imaging

DefinitionRenal angiography, also known as renal arteriography, is an imaging technique used to obtain a comprehensive view of blood flow and the vascular structure of blood vessels in the kidneys and surrounding areas.PurposeRenal angiography detects blood vessel abnormalities in the kidneys, such as aneurysms, stenosis, thrombosis, vascular tumors, and renal artery stenosis. It evaluates kidney function and guides interventional treatments like angioplasty or stent placement.Pre-Procedure...