Multidisciplinary Computational Anatomy Toward Integration of Artificial Intelligence and MCA based Medicine 1st edition by Makoto Hashizume ISBN 9811643245 978-9811643248

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ISBN 10: 9811643245
ISBN 13: 978-9811643248
Author: Makoto Hashizume 

This volume thoroughly describes the fundamentals of a new multidisciplinary field of study that aims to deepen our understanding of the human body by combining medical image processing, mathematical analysis, and artificial intelligence. Multidisciplinary Computational Anatomy (MCA) offers an advanced diagnosis and therapeutic navigation system to help detect or predict human health problems from the micro-level to macro-level using a four-dimensional, dynamic approach to human anatomy: space, time, function, and pathology. Applying this dynamic and “living” approach in the clinical setting will promote better planning for – and more accurate, effective, and safe implementation of – medical management.
Multidisciplinary Computational Anatomy will appeal not only to clinicians but also to a wide readership in various scientific fields such as basic science, engineering, image processing, and biomedical engineering. All chapters were written byrespected specialists and feature abundant color illustrations. Moreover, the findings presented here share new insights into unresolved issues in the diagnosis and treatment of disease, and into the healthy human body.

Multidisciplinary Computational Anatomy Toward Integration of Artificial Intelligence & MCA-based Medicine 1st Table of contents:

Part I: Foundations of Computational Anatomy

1. Introduction to Computational Anatomy

   • Definition and Scope of Computational Anatomy

   • History and Evolution of Computational Methods in Medicine

   • Key Applications in Clinical Practice and Research

2. Medical Imaging Technologies

   • Overview of Imaging Modalities: MRI, CT, PET, Ultrasound

   • Image Acquisition, Preprocessing, and Enhancement

   • 3D Imaging and Volumetric Representation

3. Anatomical Data and Atlases

   • Construction and Use of Anatomical Atlases

   • Standardized Anatomical Models: Templates and Landmarks

   • Organ-Specific Models: Brain, Heart, Musculoskeletal Systems

4. Geometrical and Topological Methods in Anatomy

   • Geometric Morphometrics: Shape Analysis and Quantification

   • Topological Data Analysis for Anatomical Structures

   • Deformable Models and Surface Registration

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Part II: Artificial Intelligence and Machine Learning in Anatomy

5. Introduction to Artificial Intelligence in Medicine

   • Overview of AI Technologies: Machine Learning, Deep Learning, and Reinforcement Learning

   • Applications of AI in Healthcare: Diagnosis, Treatment, and Prediction

   • Ethical Considerations in AI-Driven Medicine

6. AI Methods in Image Processing and Segmentation

   • Deep Learning for Medical Image Segmentation

   • Convolutional Neural Networks (CNNs) for Anatomical Region Detection

   • Image Registration and Fusion using AI

7. AI in Anatomical Model Generation

   • Automating Anatomical Modeling and Reconstruction

   • AI-Driven Parametric Models of Human Anatomy

   • Case Studies: AI Applications in Brain Mapping, Cardiovascular Anatomy, and Musculoskeletal Systems

8. AI for Disease Diagnosis and Prognosis

   • Role of AI in Identifying Anatomical Abnormalities

   • Predicting Disease Progression through AI Models

   • AI and Personalized Medicine: Tailoring Treatments Based on Anatomical Data

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Part III: MCA-Based Medicine (Multidisciplinary Computational Anatomy)

9. Overview of MCA-Based Medicine

   • Defining MCA-Based Medicine: An Integrative Approach

   • The Role of Interdisciplinary Collaboration in MCA

   • Clinical Applications and Benefits of MCA

10. Clinical Integration of Computational Anatomy and AI

    • AI-Assisted Diagnosis in Computational Anatomy

    • Case Studies in MCA-Based Treatment: Cancer, Neurology, Cardiology

    • Personalized Treatment Plans Powered by AI and Anatomical Data

11. Precision Medicine and Anatomical Data

    • Utilizing Anatomical Data for Precision Diagnostics

    • Role of Computational Anatomy in Tailored Therapies

    • Machine Learning and AI for Personalized Healthcare

12. Big Data and Computational Anatomy

    • Big Data in Medicine: Integrating Anatomical Data with Electronic Health Records (EHR)

    • AI-Driven Insights from Large-Scale Anatomical and Clinical Datasets

    • Challenges in Data Management, Privacy, and Security

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Part IV: Advanced Applications and Future Directions

13. Next-Generation Imaging and AI Technologies

    • Emerging Imaging Modalities and Their Impact on Anatomy Studies

    • The Role of AI in Future Imaging and Diagnostics

    • Virtual and Augmented Reality in Anatomy Education and Clinical Practice

14. Automated Surgical Planning and Simulation

    • Computational Anatomy for Preoperative Planning

    • AI in Surgical Simulation and Robot-Assisted Surgery

    • Real-Time Anatomical Navigation during Surgery

15. Artificial Intelligence in Education and Training

    • AI-Assisted Training for Medical Students and Surgeons

    • Virtual Anatomy Dissection and Learning Tools

    • Simulations for Training in Complex Anatomical Procedures

16. Future of MCA-Based Medicine and AI Integration

    • Challenges and Opportunities for AI in Medicine

    • The Evolving Role of Computational Anatomy in Healthcare

    • Integration of AI with Emerging Technologies: Blockchain, 5G, and IoT

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