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Texture analysis of iodine maps and conventional images for k-nearest neighbor classification of benign and metastatic lung nodules

机译：碘地图的纹理分析及良邻邻良肺结核k最近邻分类的常规图像

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Simon Lennartz; Alina Mager; Nils Große Hokamp; Sebastian Schäfer; David Zopfs; David Maintz; Hans Christian Reinhardt; Roman K. Thomas; Liliana Caldeira; Thorsten Persigehl;
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1. Texture analysis of iodine maps and conventional images for k-nearest neighbor classification of benign and metastatic lung nodules [J] . Simon Lennartz, Alina Mager, Nils Gro?e Hokamp, Cancer Imaging . 2021,第1期

机译：碘映射和常规图像的纹理分析良性和转移性肺结节的k最近邻分类
2. Quantitative Assessment of Thyroid Nodules Using Dual-Energy Computed Tomography: Iodine Concentration Measurement and Multiparametric Texture Analysis for Differentiating between Malignant and Benign Lesions [J] . Hayato Tomita, Hirofumi Kuno, Kotaro Sekiya, International journal of endocrinology . 2020,第2期

机译：使用双能计算断层扫描的甲状腺结节的定量评估：碘浓度测量和差异良性病变区分中的多体纹理分析
3. The Performance Analysis of K-Nearest Neighbors (K-NN) Algorithm for Motor Imagery Classification Based on EEG Signal [J] . Nurul E’zzati Md Isa, Amiza Amir, Mohd Zaizu Ilyas, MATEC Web of Conferences . 2017,第1期

机译：基于EEG信号的K-intembors（K-NN）算法的k - 最近邻居分类算法的性能分析
4. Classification of malignant-benign pulmonary nodules in lung CT images using an improved random forest (Use style: Paper title) [C] . Huihui Hu, Shengdong Nie International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery . 2017

机译：使用改进的随机森林对肺部CT图像中的恶性良性肺结节进行分类（使用方式：论文标题）
5. Comparison of the utility of regression analysis and k-nearest neighbor technique to estimate above-ground biomass in pine forests using Landsat ETM+ imagery. [D] . Prabhu, Chitra L. 2006

机译：使用Landsat ETM +图像进行回归分析和k最近邻技术估算松树林地上生物量的效用进行比较。
6. Texture analysis of iodine maps and conventional images for k-nearest neighbor classification of benign and metastatic lung nodules [O] . Simon Lennartz, Alina Mager, Nils Große Hokamp, 2021

机译：碘地图的纹理分析及良邻邻良肺结核k最近邻分类的常规图像
7. Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neural network with transfer learning [O] . Mizuho Nishio, Osamu Sugiyama, Masahiro Yakami, 2018

机译：计算机辅助诊断良性结节，原发性肺癌和转移肺癌在不同图像大小与转移学习的不同图像尺寸

Texture analysis of iodine maps and conventional images for k-nearest neighbor classification of benign and metastatic lung nodules

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