• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

Deep learning model for predicting lymph node metastasis around rectal cancer based on rectal tumor core area and mesangial imaging features.

作者信息

Guo Lili, Fu Kuang, Wang Wenjia, Zhou Li, Chen Lu, Jiang Miaomiao

机构信息

Department of Magnetic Resonance Imaging Diagnostic, The 2nd Affiliated Hospital of Harbin Medical University, Baojian Road, Nangang District, Harbin, 150086, China.

MR Research Center China, GE HealthCare, Tongjinan No.1 Road, Beijing, China.

出版信息

BMC Med Imaging. 2025 Sep 1;25(1):361. doi: 10.1186/s12880-025-01878-9.

DOI:10.1186/s12880-025-01878-9
PMID:40890619
Abstract
摘要

相似文献

1
Deep learning model for predicting lymph node metastasis around rectal cancer based on rectal tumor core area and mesangial imaging features.基于直肠肿瘤核心区域和系膜成像特征的直肠癌周围淋巴结转移预测深度学习模型
BMC Med Imaging. 2025 Sep 1;25(1):361. doi: 10.1186/s12880-025-01878-9.
2
MRI-based scoring systems for selective lateral lymph node dissection in locally advanced low rectal cancer after neoadjuvant chemoradiotherapy.新辅助放化疗后局部晚期低位直肠癌选择性侧方淋巴结清扫的基于MRI的评分系统
Eur Radiol. 2025 Feb 12. doi: 10.1007/s00330-025-11439-x.
3
Lymph node morphology as an MRI biomarker for microsatellite instability in rectal cancer.淋巴结形态作为直肠癌微卫星不稳定性的MRI生物标志物
Abdom Radiol (NY). 2025 Aug 14. doi: 10.1007/s00261-025-05161-x.
4
A 3D deep learning model based on MRI for predicting lymphovascular invasion in rectal cancer.一种基于磁共振成像（MRI）的3D深度学习模型，用于预测直肠癌中的淋巴管侵犯。
Med Phys. 2025 Jul;52(7):e17882. doi: 10.1002/mp.17882. Epub 2025 May 20.
5
Predicting Recurrence in Locally Advanced Rectal Cancer Using Multitask Deep Learning and Multimodal MRI.使用多任务深度学习和多模态磁共振成像预测局部晚期直肠癌的复发
Radiol Imaging Cancer. 2025 May;7(3):e240359. doi: 10.1148/rycan.240359.
6
Automatic segmentation of rectal tumor on diffusion-weighted images by deep learning with U-Net.基于 U-Net 的深度学习自动分割扩散加权图像中的直肠肿瘤。
J Appl Clin Med Phys. 2021 Sep;22(9):324-331. doi: 10.1002/acm2.13381. Epub 2021 Aug 3.
7
Comparative analysis of tumor and mesorectum radiomics in predicting neoadjuvant chemoradiotherapy response in locally advanced rectal cancer.肿瘤与直肠系膜的影像组学在预测局部晚期直肠癌新辅助放化疗反应中的对比分析
Diagn Interv Radiol. 2025 Aug 12. doi: 10.4274/dir.2025.253270.
8
The Avocado Sign: A novel imaging marker for nodal staging in rectal cancer.牛油果征：一种用于直肠癌淋巴结分期的新型影像学标志物。
Eur Radiol. 2025 Feb 26. doi: 10.1007/s00330-025-11462-y.
9
Novel deep learning radiomics nomogram-based multiparametric MRI for predicting the lymph node metastasis in rectal cancer: A dual-center study.基于深度学习放射组学列线图的多参数 MRI 预测直肠癌淋巴结转移的研究：一项双中心研究。
J Cancer Res Clin Oncol. 2024 Oct 9;150(10):450. doi: 10.1007/s00432-024-05986-x.
10
Diagnostic Utility of Diffusion-Weighted MRI and Apparent Diffusion Coefficient Values in Differentiating Metastatic From Non-metastatic Lymph Nodes in Cervical Carcinoma.扩散加权磁共振成像及表观扩散系数值在鉴别宫颈癌转移性与非转移性淋巴结中的诊断效用
Cureus. 2025 Jun 4;17(6):e85371. doi: 10.7759/cureus.85371. eCollection 2025 Jun.

本文引用的文献

1
Fighting the scanner effect in brain MRI segmentation with a progressive level-of-detail network trained on multi-site data.利用基于多站点数据训练的渐进式细节层次网络对抗脑 MRI 分割中的扫描仪效应。
Med Image Anal. 2024 Apr;93:103090. doi: 10.1016/j.media.2024.103090. Epub 2024 Jan 17.
2
Comparison of preoperative CT- and MRI-based multiparametric radiomics in the prediction of lymph node metastasis in rectal cancer.基于术前CT和MRI的多参数影像组学在预测直肠癌淋巴结转移中的比较
Front Oncol. 2023 Nov 24;13:1230698. doi: 10.3389/fonc.2023.1230698. eCollection 2023.
3
Medical image analysis using deep learning algorithms.
医学影像的深度学习算法分析。
Front Public Health. 2023 Nov 7;11:1273253. doi: 10.3389/fpubh.2023.1273253. eCollection 2023.
4
The Impact of Artificial Intelligence in Improving Polyp and Adenoma Detection Rate During Colonoscopy: Systematic-Review and Meta-Analysis.人工智能在提高结肠镜检查中息肉和腺瘤检出率方面的影响：系统评价和荟萃分析。
Asian Pac J Cancer Prev. 2023 Nov 1;24(11):3655-3663. doi: 10.31557/APJCP.2023.24.11.3655.
5
Progress in the diagnosis of lymph node metastasis in rectal cancer: a review.直肠癌淋巴结转移诊断的研究进展：综述
Front Oncol. 2023 Jul 13;13:1167289. doi: 10.3389/fonc.2023.1167289. eCollection 2023.
6
Radiomics from Mesorectal Blood Vessels and Lymph Nodes: A Novel Prognostic Predictor for Rectal Cancer with Neoadjuvant Therapy.来自直肠系膜血管和淋巴结的放射组学：新辅助治疗直肠癌的一种新型预后预测指标。
Diagnostics (Basel). 2023 Jun 6;13(12):1987. doi: 10.3390/diagnostics13121987.
7
Machine and deep learning in inflammatory bowel disease.机器和深度学习在炎症性肠病中的应用。
Curr Opin Gastroenterol. 2023 Jul 1;39(4):294-300. doi: 10.1097/MOG.0000000000000945. Epub 2023 May 8.
8
CNV-Net: Segmentation, Classification and Activity Score Measurement of Choroidal Neovascularization (CNV) Using Optical Coherence Tomography Angiography (OCTA).CNV-Net：使用光学相干断层扫描血管造影（OCTA）对脉络膜新生血管（CNV）进行分割、分类及活性评分测量
Diagnostics (Basel). 2023 Mar 31;13(7):1309. doi: 10.3390/diagnostics13071309.
9
MRI-based multiregional radiomics for predicting lymph nodes status and prognosis in patients with resectable rectal cancer.基于磁共振成像的多区域影像组学预测可切除直肠癌患者的淋巴结状态及预后
Front Oncol. 2023 Jan 4;12:1087882. doi: 10.3389/fonc.2022.1087882. eCollection 2022.
10
Performance and comparison of artificial intelligence and human experts in the detection and classification of colonic polyps.人工智能与人类专家在结直肠息肉检测和分类中的表现及比较。
BMC Gastroenterol. 2022 Dec 13;22(1):517. doi: 10.1186/s12876-022-02605-2.