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

相关实验视频

Updated: Jan 9, 2026

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.7K

扩散模型与DCGAN对于不平衡类型的肺癌CT分类:一项比较研究

Masoud Tabibian1, Tahereh Razmpour1, Rajib Saha1

  • 1Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska, United States of America.

bioRxiv : the preprint server for biology
|December 3, 2025
PubMed
概括

扩散模型在解决肺癌CT检测中的类不平衡方面优于DCGAN. 扩散模型提供卓越的回忆和一致性,对于精确的癌症查和减少错误诊断至关重要.

相关概念视频

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

Solute Carrier Transporter Family Modulates Neutrophil Metabolism During Health and Disease.

bioRxiv : the preprint server for biology·2026
Same author

Machine learning reveals proteome-encoded growth determinants underlying metabolic versatility of <i>Rhodopseudomonas palustris</i> on lignin-derived aromatics.

mSystems·2026
Same author

Conserved mechanisms of plant lipidome remodeling under heat and cold stresses revealed through a systematic review and meta-analysis.

Journal of experimental botany·2026
Same author

Diffusion models vs. DCGANs for class-imbalanced lung cancer CT classification: A comparative study.

Intelligence-based medicine·2026
Same author

Multi-omics integration in genome-scale metabolic models: a review of constraint-based approaches.

Molecular omics·2026
Same author

Artificial Neural Network Elucidates the Role of Transport Proteins in <i>Rhodopseudomonas palustris</i> CGA009 During Lignin Breakdown Product Catabolism.

Metabolites·2026

科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 肺癌CT扫描中的阶级不平衡导致偏见模型和错误诊断.
  • 良性和正常病例通常代表性不足,难以准确检测.

研究的目的:

  • 将扩散模型和深度卷积生成对抗网络 (DCGANs) 进行肺癌CT分类.
  • 通过使用现代建筑增强来解决阶级不平衡,评估它们的有效性.

主要方法:

  • 使用了IQ-OTH/NCCD数据集 (1,097张CT图像).
  • 在这两种模型中都包含了光谱正常化,自我注意和条件生成.
  • 使用图像质量指标 (FID,KL,KID,IS) 和分类性能进行评估.

主要成果:

  • 扩散模型显示出优越的图像质量和下游分类性能.
  • 两种模型都改善了良性回忆;扩散实现了完美的回忆 (1.000 ± 0.000).
  • 扩散模型保持了较高的恶性瘤检测灵敏度 (0.997 ± 0.008),差异较低.

结论:

  • 扩散模型是高风险的临床应用,如癌症查的首选方法.
  • 下游临床任务性能对于验证至关重要,仅仅超越图像质量指标.
  • 这两种生成方法都有效地减轻了医学成像数据集中的阶级不平衡.
关键词:
电脑图像扫描 (CT) 扫描阶级不平衡造成的失衡在DCGAN中使用DCGAN.深度学习是一种深度学习.扩散模型的扩散模型.肺癌是一种肺癌.医学成像医学成像综合数据 综合数据

更多相关视频

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

2.5K
Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models
03:38

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models

Published on: June 20, 2025

816

相关实验视频

Last Updated: Jan 9, 2026

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

14.7K
Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

2.5K
Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models
03:38

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models

Published on: June 20, 2025

816