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Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management.Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology.This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems.This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning.FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field

Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management.Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology.This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems.This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning.FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field

This cutting-edge reference book discusses the intervention of artificial intelligence in the fields of drug development, modified drug delivery systems, pharmaceutical technology, and medical devices development. This comprehensive book includes an overview of artificial intelligence in pharmaceutical sciences and applications in the drug discovery and development process. It discusses the role of machine learning in the automated detection and sorting of pharmaceutical formulations. It covers nanosafety and the role of artificial intelligence in predicting potential adverse biological effects.FEATURES Includes lucid, step-by-step instructions to apply artificial intelligence and machine learning in pharmaceutical sciences Explores the application of artificial intelligence in nanosafety and prediction of potential hazards Covers application of artificial intelligence in drug discovery and drug development Reviews the role of artificial intelligence in assessment of pharmaceutical formulations Provides artificial intelligence solutions for experts in the pharmaceutical and medical devices industriesThis book is meant for academicians, students, and industry experts in pharmaceutical sciences, medicine, and pharmacology.

Emerging contaminants include an extensive array of synthetic chemicals in global use, such as plastic additives, microplastics, water disinfection byproducts, pharmaceuticals, man-made nanomaterials, and UV-filters. Because of their extensive use in anthropogenic activities, these chemicals are entering the environment at alarming levels as hazardous wastes and non-biodegradable substances. This book emphasizes on the comprehensive information on emerging contaminants overview, environmental occurrence, analysis, risk assessment and toxicity assessment. Environmental, legal, health concerns of the ECs have also been covered in this book. The book also features an updated status from the industrial point of view.

Emerging contaminants include an extensive array of synthetic chemicals in global use, such as plastic additives, microplastics, water disinfection byproducts, pharmaceuticals, man-made nanomaterials, and UV-filters. Because of their extensive use in anthropogenic activities, these chemicals are entering the environment at alarming levels as hazardous wastes and non-biodegradable substances. This book emphasizes on the comprehensive information on emerging contaminants overview, environmental occurrence, analysis, risk assessment and toxicity assessment. Environmental, legal, health concerns of the ECs have also been covered in this book. The book also features an updated status from the industrial point of view.

Regulatory bodies such as the European Medicine Agency have done tremendous work in collaboration with experts from the field to develop Good Clinical Practices that apply not only in Europe but also in emerging countries. Designed to be a teaching aid and reference guide, A Practical Guide to Human Research and Clinical focuses on ethics, regulations, and guidelines.Conducting a successful clinical trial requires not only a strong basic knowledge, but also hands-on practical training. The book explains the intricate details of the subject to readers by citing concrete cases, exercises, and templates along with the theoretical aspects. Prof. M.U.R Naidu and his co-authors address all aspects of clinical trials from clinical research, drug development, and quality to methodology, biostatistics, and pharmacovigilance.