Search research articles

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 Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

相关概念视频

The Tongue and Taste Buds

The Tongue and Taste Buds

The surface of the tongue is covered with various small bumps called papillae, which either distribute what has been ingested (filiform papillae) or contain the sensory taste (or gustatory) receptor cells (fungiform, circumvallate, and foliate papillae). Embedded within each taste-related papilla are the taste buds—clusters of 30 to 100 gustatory receptor cells.

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 author

Long-term effectiveness and safety of vedolizumab in ulcerative colitis: a real-world retrospective cohort study over 2 years.

Frontiers in medicine·2026

Same author

Mitophagy in inflammatory bowel disease: regulatory mechanisms and therapeutic potential.

Frontiers in cell and developmental biology·2026

Same author

Audiological Phenotype, Natural History, and Intervention in Chinese Patients With Auditory Neuropathy Caused by OTOF Variants.

Ear and hearing·2026

Same author

Research on strategies for enhancing the competency of safety directors in EPC projects empowered by AI.

PloS one·2026

Same author

Surveillance for invasive candidiasis in China (CHIF-NET 2018-2021): rising antifungal resistance observed in a nationwide longitudinal study.

Antimicrobial agents and chemotherapy·2026

Same author

Investigation of molecular immune regulation mechanisms and therapeutic target prediction in pancreatic cancer based on bioinformatics and genetics.

Clinics (Sao Paulo, Brazil)·2026

Search research articles

相关实验视频

Updated: Jun 18, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

一种基于改进的TransUNet的新型舌膜涂层细分方法.

Jiaze Wu¹, Zijian Li¹, Yiheng Cai²

¹School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102488, China.

Sensors (Basel, Switzerland)

|July 27, 2024

概括

这项研究引入了改进的TransUNet模型,用于精确的舌头涂层细分,用于智能舌头诊断. 该模型提高了准确性和细节性,帮助自动诊断系统.

关键词:

通过TransUNet的网络.计算机视觉计算机视觉深度学习是一种深度学习.医疗图像细分医疗图像细分舌头诊断诊断舌头诊断

更多相关视频

µTongue: A Microfluidics-Based Functional Imaging Platform for the Tongue In Vivo

µTongue: A Microfluidics-Based Functional Imaging Platform for the Tongue In Vivo

Published on: April 22, 2021

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

相关实验视频

Last Updated: Jun 18, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

µTongue: A Microfluidics-Based Functional Imaging Platform for the Tongue In Vivo

µTongue: A Microfluidics-Based Functional Imaging Platform for the Tongue In Vivo

Published on: April 22, 2021

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

科学领域:

医疗成像医学成像
人工智能的人工智能
计算生物学计算生物学

背景情况:

舌头涂层分析对于诊断各种健康疾病至关重要.
自动化舌头诊断需要精确细分舌头涂层.
当前的方法在细分复杂的舌头涂层特征方面面临挑战.

研究的目的:

为复杂的舌头涂层细分开发先进的神经网络.
提高智能舌头诊断系统的准确性和自动化.

主要方法:

开发了一种改进的TransUNet模型,其中包括用于自我注意的变压器.
减法特征金字塔 (SFP) 和视觉区域增强器 (VRE) 被集成.
这些增强旨在捕获语义信息,并改进低层特征中的空间细节.

主要成果:

提出的模型实现了高性能指标:96.36%的准确性,96.26%的精度,96.76%的子得分,97.43%的回忆和93.81%的IOU.
与参考模型相比,比较和废除研究证实了优越的细分.

结论:

改进的TransUNet模型提供了复杂的舌头图像的精确细分.
这种技术有效地自动提取舌头涂层,提高诊断准确度.