EIT Signal Quality and Reconstruction Dataset and Figures with code

# EIT Signal Quality and Reconstruction Dataset This dataset accompanies the submission to *Inverse Problems* titled: "Performance Benchmarking of Five FEM Based Electrical Impedance Tomography (EIT) Image Reconstruction Techniques Using Signal Quality Metrics and Real Hardware Data" Published on 03 February 2026. Digital Object Identifier (DOI): DOI 10.1088/1361-6420/ae3798. Journal online version link: Performance Comparison Study of Electrical Impedance Tomography (EIT) Image Reconstruction Techniques Using Signal Quality Metrics and Real Hardware Data - IOPscience --- ## Contents | File Name | Description ||------------------------|-------------|| `PSNR.csv` | Peak Signal-to-Noise Ratio values across reconstruction methods and signal settings || `SSIM.csv` | Structural Similarity Index values across conditions || `CNR.csv` | Contrast-to-Noise Ratio across reconstruction methods || `RMSE.csv` | Root Mean Square Error of reconstructed images || `Coherence.csv` | Coherence between injected and received signals || `STER.csv` | Spectral Energy Ratio per condition || `THD.csv` | Total Harmonic Distortion (%) in each condition || `PhaseShift.csv` | Average phase shift (degrees) from original signals || `SNR_Comparison.csv` | Raw and filtered SNR and gain across four signal setups | --- ## Format Each `.csv` file is organized with: - **Rows** representing reconstruction methods: `BackProjection`, `GaussNewton`, `Tikhonov`, `GREIT`, `EIDORS` - **Columns** representing signal conditions: `10kHz_1Vpp`, `10kHz_5Vpp`, `50kHz_1Vpp`, `50kHz_5Vpp` --- ## License This dataset is licensed under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license. You may share, adapt, or reuse with proper attribution. --- ## Contact For questions or data clarification or any other assistance, please contact: **MD MAINUDDIN SAGAR** University of Massachusetts Dartmouth GitHub: [https://github.com/Sagar-Massachusetts](https://github.com/Sagar-Massachusetts)# 电阻抗断层成像（Electrical Impedance Tomography, EIT）信号质量与重建数据集 本数据集配套提交至《逆问题（Inverse Problems）》期刊的论文，论文标题为《基于五种有限元法的电阻抗断层成像（EIT）图像重建技术性能基准测试：结合信号质量指标与真实硬件数据》，于2026年2月3日发表，数字对象标识符（DOI）：10.1088/1361-6420/ae3798，期刊在线版本链接：《基于信号质量指标与真实硬件数据的电阻抗断层成像（EIT）图像重建技术性能比较研究》- IOPscience --- ## 数据集内容 | 文件名 | 描述 | |------------------------|-------------| | `PSNR.csv` | 各重建方法与信号设置下的峰值信噪比（Peak Signal-to-Noise Ratio, PSNR）数值 | | `SSIM.csv` | 各实验条件下的结构相似性指数（Structural Similarity Index, SSIM）数值 | | `CNR.csv` | 各重建方法下的对比度噪声比（Contrast-to-Noise Ratio, CNR）数值 | | `RMSE.csv` | 重建图像的均方根误差（Root Mean Square Error, RMSE） | | `Coherence.csv` | 注入信号与接收信号间的相干性 | | `STER.csv` | 各实验条件下的谱能量比（Spectral Energy Ratio, STER） | | `THD.csv` | 各实验条件下的总谐波失真（Total Harmonic Distortion, THD，单位：%） | | `PhaseShift.csv` | 原始信号的平均相移（单位：度） | | `SNR_Comparison.csv` | 四种信号设置下的原始与滤波后信噪比及增益数值 | --- ## 数据格式 每个CSV文件的组织结构如下： - **行**代表图像重建方法，分别为：`BackProjection`（反向投影法）、`GaussNewton`（高斯牛顿法）、`Tikhonov`（蒂霍诺夫正则化法）、`GREIT`、`EIDORS` - **列**代表信号实验条件，分别为：`10kHz_1Vpp`、`10kHz_5Vpp`、`50kHz_1Vpp`、`50kHz_5Vpp` --- ## 授权协议 本数据集采用**知识共享署名4.0国际许可协议（Creative Commons Attribution 4.0 International, CC BY 4.0）**进行授权。您可在标注原作者的前提下进行分享、改编或复用。 --- ## 联系方式 如有疑问、数据澄清或其他协助需求，请联系： **MD MAINUDDIN SAGAR**，美国马萨诸塞大学达特茅斯分校，GitHub主页：https://github.com/Sagar-Massachusetts