Smart Microscopy, AI, and Robotics

Priyadarshini Pattanaik is a Senior Lecturer at the Berlin School of Business and Innovation, Germany. Her research focuses on quantitative analysis and the development of machine learning algorithms using deep neural networks and graphical models for visual computing, with applications in medical image analysis and disease detection.She previously served as a Postdoctoral Scientist at IMT Atlantique, France, within the Image and Information Processing department of the LaTIM research group (2020–2022). Her work addressed key challenges in the musculoskeletal (MSK) field, particularly exploring the relationship between joint shape and function through advanced computational methods. Earlier, she worked as a Postdoctoral Fellow collaborating with several academic and industry partners, including Télécom SudParis, Université Paris-Saclay, the Centre for Mathematical Morphology at Mines ParisTech, and the company TRIBVN (2019). She has authored numerous publications in high-impact SCI and Scopus-indexed journals and international conferences.Dr. Chiranji Lal Chowdhary is Professor in the School of Computer Science Engineering and Information Systems at Vellore Institute of Technology, India. He has more than 20 years of academic and research experience in artificial intelligence, machine learning, deep learning, computer vision and intelligent systems. His research spans industrial AI, Industry 4.0 technologies, smart healthcare and data-driven decision-making systems. He has published extensively in international journals and conferences and has edited several scholarly volumes. He has supervised doctoral and postgraduate researchers and contributes actively to research evaluation, curriculum development and academic leadership. His expertise in intelligent systems and digital transformation aligns closely with the themes of AI-enabled industrial ecosystems and lifecycle intelligence explored in this book. Dr. Gaurav Agarwal is Professor and Program Co-Chair (B.Tech CSE) at Galgotias University, Greater Noida, India. He holds a Ph.D. in Computer Science and Engineering from IIT (ISM) Dhanbad and brings over 21 years of academic and leadership experience, including roles as Associate Head, Academic Head, and Central NBA Coordinator (2018–2022). His research spans speech signal processing, genetic algorithms, and web search engines. He has published over 40 papers in reputed journals and conferences and holds eight Indian patents (six granted). His honors include the IRNet Young Investigator Award and recognitions from Rotary International.

• 1. Introduction to Microscopy and enhanced cell analysis in contrast microscopy images.2. Study of Automated Microscopic Diagnosis with machine-microscope integration in imaging systems3. Image Acquisition, Image Segmentation, Image Classification, and Image Analysis and Preprocessing Methods.4. Robotics in Microscopy: Automated Slide Handling, Scanning, and Imaging Workflow Automation5. Role of big data and statistical analysis for handling large medical datasets of microscopic images.6. Role of Artificial Intelligence (AI), Deep Learning (DL), and Machine Learning (ML) for automated disease detection.7. AI-Based Detection of Blood Disorders and Infectious Diseases: Malaria, Leukemia, TB, and Beyond8. Robotics-AI Integration for automated disease detection for early and accurate treatment.9. The use of AI for automated Histopathology and cytopathology analysis.10. Performance measurements in system validation, clinical settings, and workflow integration.11. Issues related to ethics, regulation, and safety considerations of AI in healthcare12. Production and development of novel, precise drug discovery and therapeutic targets through AI from microscopic disease insights.13. Potential Future Scope of AI in smart labs, automated diagnostics, and global health impact.14. Explainable and Interpretable AI for Microscopy: Transparency, Bias Mitigation, and Trust in Automated Diagnostics15. Human–AI Interaction, Clinical Adoption, and Interoperability Standards in Smart Microscopy Systems