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Table of Contents: “...-- Effect on care timing -- Effect on tumor stage and survival -- Possibilities for increasing effectiveness of CRC rapid pathways -- Conclusions -- References -- Section C: Diagnosis and staging -- Section C.I: Current diagnosis methods in colorectan cancer -- Chapter 8: Colon capsule endoscopy -- Introduction -- Technical characteristics of the second-generation colon capsule -- Preparation of the patient -- Comparative studies between colon capsule endoscopy and colonoscopy -- Comparative studies between CCE and colonography by computerized axial tomography -- Current indications and contraindications of the colon capsule endoscopy: Future perspectives -- Conclusions -- References -- Chapter 9: Endoscopic ultrasound in CRC -- Outline of technique -- EUS for rectal cancer staging -- Degree of invasion of intestinal wall (uT) -- Affectation of local adenopathies (uN) -- Significance of the circumferential resection margin -- EUS for assessment of neoadjuvant therapy response -- Interventional EUS -- EUS-FNA initial diagnosis and recurrence -- Differential diagnosis and diagnosis of neoplastic affectation of adenopathies -- Diagnosing tumor recurrence -- Drainage of postsurgical fluid collections -- Extrahepatic bile duct drainage -- Conclusion -- References -- Chapter 10: CT-Colonography (CTC): Technical requirements, indications and current status -- Introduction -- Technical requirements -- Preparation of the colon -- Distension of the colon -- Image acquisition -- Software and tools -- Indications for virtual colonoscopy -- Clinically significant findings in CTC -- Polyps -- Cancers -- Submucosal lesions....”
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Table of Contents: “...129 5.13 Conclusion and Future Scope 130 6 The Contribution of Computer Vision in the Manufacturing Industries and the Scope for Further Excellence 135 6.1 Introduction 136 6.2 Components of a Machine Vision Systems 138 6.3 Image Formation 141 6.4 Computer vision algorithms 141 6.5 Use Case of the Computer Vision in Industries 141 6.5.1 Product assembly 141 6.5.2 Defect detection 142 6.5.3 3D Vision system 144 6.5.4 Vision-guided robots 144 6.5.5 Predictive maintenance 145 6.6 Safety and Security Standards 145 6.7 Packaging Standards 147 6.8 Barcode Analysis 148 6.9 Inventory Management 148 6.10 Optimizing Supply Chains 149 6.11 Quality Inspection with Computer Vision 149 6.12 Computer Vision during the Covid-19 Pandemic 150 6.13 Computer Vision in the Automotive Industry 151 6.13.1 Press shop 152 6.13.2 Body shop 153 6.13.3 Paint shop 154 6.13.4 Final assembly shop 154 6.14 Computer Vision Performance Metrics 155 6.14.1 Intersection over union (IoU) 155 6.14.2 Precision 155 6.14.3 Recall 156 6.14.4 F1 score 156 6.15 Conclusion 158 7 Waste Management 4.0: An Industry Automation Approach to the FutureWaste Management System 163 7.1 Introduction 164 7.2 Exploring CPS 166 7.2.1 CPS 166 7.2.2 Drawbacks of CPS 167 7.3 Industry 4.0 Environment 168 7.4 Challenges in the Waste Management Industry 169 7.5 Applications of CPS in the Waste Management Industry 171 7.6 Influence of Industry 4.0 on the Waste Management Industry 172 7.7 Barriers to Implementing Industry 4.0 in the Waste Management Industry 174 7.8 Case Study: Machine Learning for Waste Management 175 7.9 Conclusion 177 8 Industrial Internet of Things (IIoT) for E-waste Recycling System 181 8.1 Introduction 181 8.2 Background Study 182 8.3 IIoT Working 182 8.4 IIoT Security 183 8.4.1 Risks and challenges of IIoT 183 8.4.2 Difference between IoT and IIoT 184 8.4.3 IIoT applications and examples 184 8.5 Industries using IIoT 185 8.6 Advantages and Disadvantages of IIoT 186 8.6.1 Hindrances of IIoT 188 8.7 Case Study - IoT for E-waste Recycling System 189 8.8 Future Trends of IIoT 192 8.9 Conclusion 195 9 A Multi-hazard Industry Assessment System Based on Unmanned Aerial Vehicles (UAVs) for Bridges Crossing Seasonal Rivers 199 9.1 Introduction 200 9.2 Literature Survey 203 9.3 Methodology 206 9.3.1...”
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