Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or playing an...
Organization of the Brain01:31

Organization of the Brain

The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
Hindbrain
The hindbrain, located at the base of the brain, plays a vital role in regulating automatic processes that sustain life. It includes the medulla oblongata, which is essential for...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same journal

A novel carotid artery catheterization device for intracranial drug delivery in rats and mice.

Journal of neuroscience methods·2026
Same journal

Event-related potential dynamics of unilateral lower limb movement with functional connectivity analysis.

Journal of neuroscience methods·2026
Same journal

Design and validation of a reaching-task system for quantifying wrist extension recovery after radial nerve repair in nonhuman primates.

Journal of neuroscience methods·2026
Same journal

Chromate/Fluoro-Jade: A high resolution and contrast fluorescent staining method for localizing myelinated fibers in paraffin embedded brain tissue sections.

Journal of neuroscience methods·2026
Same journal

Mesenchymal stem cell-derived small extracellular vesicles in spinal cord injury: From molecular repair mechanisms to standardized translational development.

Journal of neuroscience methods·2026
Same journal

Neurochemistry and post-mortem neurotransmitters: toward the study of neurochemical connectivity.

Journal of neuroscience methods·2026

相关实验视频

Updated: Jul 23, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

一个优化的等级注意力辅助深度学习模型用于大脑组织分类.

Divya Sundar V S1, Vijayachamundeeswari V2

  • 1Department of Computer Science and Engineering, Saveetha Engineering College, Thandalam, Chennai-602105, India.

Journal of neuroscience methods
|February 25, 2026
PubMed
概括

这项研究引入了一种优化的深度学习模型,用于精确的脑组织细分和MRI扫描中的分类. 这种新的方法在检测大脑组织异常方面取得了很高的准确性,提高了诊断能力.

关键词:
脑组织细分 脑组织细分囊网络是一个囊网络.科蒂优化算法 科蒂优化算法化积累桥是什么意思层次化的注意力.剩余的块是剩余的块.

相关实验视频

Last Updated: Jul 23, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

科学领域:

  • 医学成像分析 医学成像分析
  • 深度学习应用程序
  • 神经科学是一个神经科学.

背景情况:

  • 在磁共振成像 (MRI) 中精确的脑组织分化对于医疗应用至关重要.
  • 由于不同类型的扫描仪和采购程序的不一致性,现有的方法面临限制.
  • 复杂的大脑组织结构需要先进的细分技术.

研究的目的:

  • 开发一种有效,优化的层次深度学习方法,用于检测大脑组织异常.
  • 为了提高MRI脑组织分类和细分的精度.
  • 为了解决当前处理扫描器间变量的方法的局限性.

主要方法:

  • 使用min-max正常化进行MRI图像的预处理.
  • 一种新的混合细分方法,剩余的融合积累U-net桥梁模块 (ResFAU-net),结合剩余块,注意力门和融合积累桥梁模块.
  • 使用基于层次的注意力修改的卷积层级囊网络 (HAMC) 的分类,集成CNN和层次的注意力.

主要成果:

  • 该模型在BRATS2020数据集上进行了评估.
  • 性能被验证使用指标,包括子得分,十字路口超过联盟 (IoU),准确性,精度,灵敏度,特异性和F1得分.
  • 拟议的模型在各种指标上表现出强的表现.

结论:

  • 开发的层次深度学习模型有效地细分和分类异常的大脑组织.
  • 该模型实现了96.29%的高IOU得分和99.03%的准确性.
  • 这种方法显示了改善脑组织异常检测的巨大潜力.