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Add x-ray-preprocessing && Fix Appendix Chapter && Update readme
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‎README.md‎

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- **1.4** 医学影像中的伪影 — 识别和理解成像伪影
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#### 第2章 模态特定的预处理
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- **2.1** CT：从探测器信号到校正投影 ✨ **新增**
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- **2.1** CT：从探测器信号到校正投影
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- 从光子采集到校准投影数据的完整工作流程
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- **2.2** MRI k-空间预处理 ✨ **新增**
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- K空间数据生成、欠采样策略与滤波技术
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#### 第3章 图像重建算法
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- **3.1** 解析重建：滤波反投影（FBP）
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- CT重建的数学原理与滤波器选择
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- **3.2** 迭代重建：代数与压缩感知方法 ✨ **新增**
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- POCS、SART等迭代算法原理与实现
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#### 第4章 多模态重建实践
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- **4.1** 数据集介绍与实验准备
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- **4.2** 案例一：CT重建全流程 ✨ **新增**
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- 从原始投影数据到重建图像的完整流程
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- **4.3** 案例二：MRI K空间成像与重建实验 ✨ **新增**
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- 欠采样策略、重建算法与质量评估
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#### 第5章 基于深度学习的后处理
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- **5.1** 预处理 — 针对 AI 模型的模态特定数据准备
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- **5.4** 图像增强与恢复 — 去噪和超分辨率技术
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### 🚀 即将推出
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- **2.2** MRI k-空间预处理
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- **2.3** X-ray 直接成像校正
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- **第3章** 按模态分类的图像重建算法
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- **第4章** 多模态重建实践
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- **4.4** 更多重建案例（PET、超声等）
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- **第6章** 高级主题与前沿技术
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## 🤝 如何贡献
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‎README_en.md‎

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- **1.4** Artifacts in Medical Imaging — Identifying and understanding imaging artifacts
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#### Chapter 2: Modality-Specific Preprocessing
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- **2.1** CT: From Detector Signal to Corrected Projection ✨ **NEW**
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- **2.1** CT: From Detector Signal to Corrected Projection
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- Complete workflow from photon acquisition to calibrated projection data
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- **2.2** MRI k-space Preprocessing ✨ **NEW**
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- K-space data generation, undersampling strategies, and filtering techniques
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#### Chapter 3: Image Reconstruction Algorithms
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- **3.1** Analytic Reconstruction: Filtered Back Projection (FBP)
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- Mathematical principles of CT reconstruction and filter selection
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- **3.2** Iterative Reconstruction: Algebraic and Compressed Sensing Methods ✨ **NEW**
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- POCS, SART and other iterative algorithms: principles and implementation
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#### Chapter 4: Multi-Modality Reconstruction Practice
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- **4.1** Dataset Introduction and Experiment Preparation
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- **4.2** Case Study 1: Complete CT Reconstruction Workflow ✨ **NEW**
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- Full pipeline from raw projection data to reconstructed images
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- **4.3** Case Study 2: MRI K-space Imaging and Reconstruction Experiments ✨ **NEW**
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- Undersampling strategies, reconstruction algorithms, and quality assessment
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#### Chapter 5: Deep Learning Post-processing
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- **5.1** Preprocessing — Modality-specific data preparation for AI models
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- **5.4** Image Enhancement and Recovery — Denoising and super-resolution techniques
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### 🚀 Coming Soon
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- **2.2** MRI k-space Preprocessing
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- **2.3** X-ray Direct Imaging Correction
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- **Chapter 3** Image Reconstruction Algorithms by Modality
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- **Chapter 4** Multi-Modality Reconstruction Practice
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- **4.4** More Reconstruction Cases (PET, Ultrasound, etc.)
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- **Chapter 6** Advanced Topics and Cutting-Edge Techniques
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## 🤝 Contributing
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‎docs/.vitepress/config.ts‎

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items: [
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{ text: '2.1 CT/X-ray：正弦图与探测器校正', link: '/guide/ch02/01-ct-preprocessing' },
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{ text: '2.2 MRI：K空间去卷绕与填充', link: '/guide/ch02/02-mri-preprocessing' },
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{ text: '2.3 PET/US：衰减校正与降噪', link: '/guide/ch02/03-pet-us-preprocessing' }
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{ text: '2.3 PET/US：衰减校正与降噪', link: '/guide/ch02/03-pet-us-preprocessing' },
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{ text: '2.4 X射线：直接成像的校正', link: '/guide/ch02/04-xray-preprocessing' }
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]
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},
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{
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items: [
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{ text: '2.1 CT/X-ray: Sinogram & Detector Correction', link: '/en/guide/ch02/01-ct-preprocessing' },
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{ text: '2.2 MRI: k-Space Unwrapping & Padding', link: '/en/guide/ch02/02-mri-preprocessing' },
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{ text: '2.3 PET/US: Attenuation Correction & Denoising', link: '/en/guide/ch02/03-pet-us-preprocessing' }
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{ text: '2.3 PET/US: Attenuation Correction & Denoising', link: '/en/guide/ch02/03-pet-us-preprocessing' },
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{ text: '2.4 X-ray: Direct Imaging Correction', link: '/en/guide/ch02/04-xray-preprocessing' }
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{

‎docs/en/guide/appendix/A-formula.md‎

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# A Key Formulas
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> title: A Key Formulas
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>
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> description: Summarizes the most common, important, and cross-modality universal formulas in medical imaging. Enables readers to quickly consult and understand mathematical derivations when reading the main tutorial. Suitable for beginners to quickly establish a formula framework.
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---
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title: Appendix A Key Formulas
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description: Summarizes the most common, important, and cross-modality universal formulas in medical imaging. Enables readers to quickly consult and understand mathematical derivations when reading the main tutorial. Suitable for beginners to quickly establish a formula framework.
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---
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# A Key Formulas
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# Appendix A: Key Formulas
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# 1. Introduction
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‎docs/en/guide/appendix/B-tool-Installation.md‎

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# B Tool Installation
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> title: B Tool Installation
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>
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> description: Introduces installation methods for common tools.
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---
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title: Appendix B Tool Installation
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description: Introduces installation methods for common tools.
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---
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# B Tool Installation
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# Appendix B: Tool Installation
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# 1. Introduction
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‎docs/en/guide/appendix/C-dataset/C-1-CT.md‎

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# C-1 CT Type Datasets
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---
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title: Appendix C-1 CT Type Datasets
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description: Introduces CT type datasets
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---
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> title: C-1 CT Type Datasets
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> description: Introduces CT type datasets
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# Appendix C-1: CT Type Datasets
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# 1. LIDC-IDRI (Lung CT Nodule Database)
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‎docs/en/guide/appendix/C-dataset/C-2-MRI.md‎

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# C-2 MRI Type Datasets
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---
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title: Appendix C-2 MRI Type Datasets
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description: Introduces MRI type datasets
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> description: Introduces MRI type datasets
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# Appendix C-2: MRI Type Datasets
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# 1. BraTS (Brain Tumor MRI Segmentation Dataset)
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‎docs/en/guide/appendix/C-dataset/C-3-X-ray.md‎

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# C-3 X-ray Type Datasets
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title: Appendix C-3 X-ray Type Datasets
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description: Introduces X-ray type datasets
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# Appendix C-3: X-ray Type Datasets
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# 3. CheXpert (Large-scale Chest X-ray Lesion Detection Dataset)
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‎docs/en/guide/appendix/C-dataset/C-4-Multimodal.md‎

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# C-4 Multimodal Datasets
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title: Appendix C-4 Multimodal Datasets
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description: Introduces multimodal datasets
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> description: Introduces multimodal datasets
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# Appendix C-4: Multimodal Datasets
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# 1. ADNI (Alzheimer's Disease Neuroimaging)
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‎docs/en/guide/appendix/D-glossary.md‎

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# D Glossary
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title: Appendix D Glossary
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description: Introduces common terminology
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# Appendix D: Glossary
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|English Term|Explanation|
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| --------------------------------| ----------------------------------------------------------------------|

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