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

Classification of Bones

Classification of Bones

The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The long...

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

Injecting reasoning into vision-language models via weight-decomposed merging.

Neural networks : the official journal of the International Neural Network Society·2026

Same author

Non-invasive diagnostic model for myocarditis using cardiac magnetic resonance radiomics.

Quantitative imaging in medicine and surgery·2026

Same author

Author Correction: Towards clinical-level interpretation of dental panoramic radiography using an instance-guided vision-language model.

Nature biomedical engineering·2026

Same author

DiffRES: Unleashing Text-to-Image Diffusion Models for Generative Referring Expression Segmentation Without Information Leakage.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

LoRASculpt: Harmonious Low-Rank Adaptation for Multimodal Large Language Models.

IEEE transactions on pattern analysis and machine intelligence·2026

Same author

Towards clinical-level interpretation of dental panoramic radiography using an instance-guided vision-language model.

Nature biomedical engineering·2026

Search research articles

相关实验视频

Updated: Jun 29, 2026

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

利用文本解剖学知识来实现类不平衡的半监督多器官细分.

Yuliang Gu, Weilun Tsao, Yepeng Liu

IEEE transactions on medical imaging

|January 12, 2026

概括

本研究引入了一种新的方法,使用多模态大语言模型 (MLLM) 来提取半监督的多器官细分的解剖学先验,通过利用文本见解来提高器官本地化和形状可信度,显著提高准确性.

科学领域:

医学图像分析医学图像分析
人工智能的人工智能
计算解剖学的计算解剖学

背景情况:

半监督的多器官细分由于不平衡的阶级分布而面临挑战.
整合解剖学知识是解决这些细分困难的关键策略.

研究的目的:

探索使用多模态大语言模型 (MLLM) 来提取解剖学先验.
通过结合文本解剖见解来改善半监督的多器官细分.

主要方法:

使用GPT-4o生成器官位置关系和形状的文本描述作为解剖学先验.
将这些文本先验集成到一个细分模型的头部.
采用对比学习,使文字先验与视觉特征保持一致.

主要成果:

拟议的方法在最先进的方法中显示出显著的性能改进.
器官间位置先验有助于定位较小的器官相对于较大的器官.
器官形状的先验增强了学习的形态结构的解剖学可信性.

结论:

来自MLLM的解剖学先验对于增强半监督多器官细分是有效的.
通过对比学习整合文本和视觉特征可以提高细分精度和解剖正确性.

更多相关视频

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

相关实验视频

Last Updated: Jun 29, 2026

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

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024