现代信息技术引入中医（TCM）不仅可以获得中医数千年的客观进程，同时对现代医学也提供了新的发现。这本书是基于作者十余年的研究成果，全面、系统介绍中医数据计算机处理和分析的优秀著作。
本书分4个部分共10章，主要介绍中医舌象、脉冲信号和呼吸气味信号三种类型的数据，通过计算机数据分析（CTDA）、图像分析、脉冲分析和气味分析，实现中医数据化的基本理论、技术和方法。第一部分（第1章）是对本书内容的简要介绍；第2部分（第2章~第5章）介绍中医舌诊诊断特征，按颜色、纹理、形状和其他病理特点进行数据提取和分析；第3部分（第6章~第8章）讲述中医脉诊的脉冲数据分析；第4部分（第9章~第10章）对呼吸气味数据的采集、分析进行的讲解。
本书研究基础扎实，内容翔实、严谨。可作为计算机中医药数据分析领域研究人员的专业用书，也可供计算机图像识别、中医学等专业研究生参考使用。
- 目录
- Front Matter
- PART I: DIAGNOSIS METHODS IN TRADITIONAL CHINESE MEDICINE
- Chapter 1 Introduction
- 1.1 Diagnosis Methods in Traditional Chinese Medicine
- 1.2 Computerized TCM Diagnosis
- 1.3 Summary
- References
- PART II: COMPUTERIZED TONGUE IMAGE ANALYSIS
- Chapter 2 Tongue Image Acquisition and Preprocessing
- 2.1 Tongue Image Acquisition
- 2.2 Color Correction
- 2.3 Summary
- References
- Chapter 3 Automated Tongue Segmentation
- 3.1 Bi-Elliptical Deformable Contour
- 3.2 Snake with Polar Edge Detector
- 3.3 Gabor Magnitude-based Edge Detection and Fast Marching
- 3.4 Summary
- References
- Chapter 4 Tongue Image Feature Analysis
- 4.1 Color Feature Analysis
- 4.2 Tongue Texture Analysis
- 4.3 Tongue Shape Analysis
- 4.4 Extraction of Other Local Pathological Features
- 4.5 Summary
- References
- Chapter 5 Computerized Tongue Diagnosis
- 5.1 Bayesian Network for Computerized Tongue Diagnosis
- 5.2 Diagnosis Based on Hyperspectral Tongue Images
- 5.3 Summary
- References
- PART III: COMPUTERIZED PULSE SIGNAL ANALYSIS
- Chapter 6 Pulse Signal Acquisition and Preprocessing
- 6.1 Pressure Pulse Signal Acquisition
- 6.2 Baseline Wander Correction of Pulse Signals
- 6.3 Summary
- References
- Chapter 7 Feature Extraction of Pulse Signals
- 7.1 Spatial Feature Extraction
- 7.2 Frequency Feature Extraction
- 7.3 AR Model
- 7.4 Gaussian Mixture Model
- 7.5 Summary
- References
- Chapter 8 Classification of Pulse Signals
- 8.1 Pulse Waveform Classification
- 8.2 Arrhythmic Pulses Detection
- 8.3 Combination of Heterogeneous Features for Pulse Diagnosis
- 8.4 Summary
- References
- PART IV: COMPUTERIZED ODOR SIGNAL ANALYSIS
- Chapter 9 Breath Analysis System: Design and Optimization
- 9.1 Breath Analysis
- 9.2 Design of Breath Analysis System
- 9.3 Sensor Selection
- 9.4 Summary
- References
- Chapter 10 Feature Extraction and Classification of Breath Odor Signals
- 10.1 Feature Extraction of Odor Signals
- 10.2 Common Classifiers for Odor Signal Classification
- 10.3 Sparse Representation Classification
- 10.4 Support Vector Ordinal Regression
- 10.5 Evaluation on Classification methods
- 10.6 Summary
- References
- Index
