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.
- 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
Table of Contents
1. An Introduction to Medical Image Analysis in 3D
[Upasana Sinha, Kamal Mehta, and Prakash C. Sharma]
2. Automated Epilepsy Seizure Detection from EEG Signals Using Deep CNN Model
[Saroj Kumar Pandey, Rekh Ram Janghel, Archana Verma, Kshitiz Varma, and Pankaj Kumar Mishra]
3. Medical Image De-Noising Using Combined Bayes Shrink and Total Variation Techniques
[Devanand Bhonsle, G. R. Sinha, and Vivek Kumar Chandra]
4. Detection of Nodule and Lung Segmentation Using Local Gabor XOR Pattern in CT Images
[Laxmikant Tiwari, Rohit Raja, Vineet Awasthi, and Rohit Miri]
5. Medical Image Fusion Using Adaptive Neuro Fuzzy Inference System
[Kamal Mehta, Prakash C. Sharma, and Upasana Sinha]
6. Medical Imaging in Healthcare Applications
[K. Rawal, G. Sethi, and D. Ghai]
7. Classiﬁcation of Diabetic Retinopathy by Applying an Ensemble of Architectures
[Rahul Hooda and Vaishali Devi]
8. Compression of Clinical Images Using Different Wavelet Function
[Munish Kumar and Sandeep Kumar]
9. PSO-Based Optimized Machine Learning Algorithms for the Prediction of Alzheimer’s Disease
[Saroj Kumar Pandey, Rekh Ram Janghel, Pankaj Kumar Mishra, Kshitiz Varma, Prashant Kumar, and Saurabh Dewangan]
10. Parkinson’s Disease Detection Using Voice Measurements
[Raj Kumar Patra, Akansha Gupta, Maguluri Sudeep Joel, and Swati Jain]
11. Speech Impairment Using Hybrid Model of Machine Learning
[Renuka Arora, Sunny Arora, and Rishu Bhatia]
12. Advanced Ensemble Machine Learning Model for Balanced BioAssays
[Lokesh Pawar, Anuj Kumar Sharma, Dinesh Kumar, and Rohit Bajaj]
13. Lung Segmentation and Nodule Detection in 3D Medical Images Using Convolution Neural Network
[Rohit Raja, Sandeep Kumar, Shilpa Rani, and K. Ramya Laxmi]
Rohit Raja is working as associate professor in the IT Department at the Guru Ghasidas, Vishwavidyalaya, Bilaspur (CG). He has done PhD in Computer Science and Engineering in 2016 from C. V. Raman University, India. His primary research interests include face recognition, signal processing and networking and data mining. He has successfully ﬁled 10 patents. He has 80 research publications to his credit in various international/national journals (including IEEE, Springer etc.) and in proceedings of reputed international/national conferences (including Springer and IEEE). He was invited thrice as a guest in Scopus indexed IEEE/Springer conferences. He has been invited four times, being an expert, in various colleges and universities in India. He has the following awards to his credit: "Excellence in Research" Award under the category of HEI Professor by Auropath Global Awards, 2019; the "Distinguished Research Award", I2OR Awards 2019, during the 4th International Conclave on Interdisciplinary Research for Sustainable Development 2020 (IRSD 2020); and the second runner up award in grand ﬁnale of Smart India Hackathon, 2017, Ministry of Skill Development and Entrepreneurship, Government of India.
He is a member of professional international society including IEEE, ISTE, CSI, ACM etc. He is editor/reviewer of many peer-reviewed and refereed journals (including IEEE, Springer, enderscience).
Sandeep Kumar is presently working as a professor in the Department of Electronics & Communication Engineering, Sreyas Institute of Engineering & Technology, Hyderabad, India. He has good academic and research experience in various areas of electronics and communication. His areas of research include embedded system, image processing, biometrics and machine learning. He has successfully ﬁled eight patents – seven national and one international. He was invited thrice as a guest in Scopus indexed IEEE/Springer conferences. He has been invited four times, being an expert, in various colleges and universities in India. He has published 70 research papers in various international/national journals (including IEEE, Springer etc.) and in the proceedings of the reputed international/national conferences (including Springer and IEEE). He has been awarded the "Best Paper Presentation" award in Nepal and in India, respectively, 2017 and 2018. He has been awarded the "Best Performer Award" in Hyderabad, India, 2018. He has also been awarded the "Young Researcher Award" in Thailand, 2018, and the "Best Excellence Award" in Delhi, 2019. He is an active member of 17 professional international societies. He has been nominated in the board of editors/reviewers of 25 peer-reviewed and refereed journals (including IEEE and Springer). He has conducted three international conferences and six workshops. He is also attended 24 seminars, workshops and short-term courses in IITs etc. He is a research guide for a number of Ph.D and M.Tech students.
Shilpa Rani is presently working as an assistant professor in the Department of Computer Science and Engineering, Neil Gogte Institute of Technology, Hyderabad, India. She has good academic and research experience in various areas of computer science. Her area of research includes image processing, IOT, and big data. She has successfully ﬁled three patents. She has published a number of research papers in various international/national journals (including IEEE, Springer etc.). She has been awarded the gold medal in 2012 during M.Tech. She is an active member of 10 professional international societies. She has been nominated in the board of editors/reviewers of four peer-reviewed and refereed journals. She has also attended 15 seminars, workshops and short-term courses in JNTUH and others. She has published two text books Logical & Functional Programming, Ashirwad Publication, 2009–2010 and Software Engineering, VAYU Education of India, 2011. Her third book has been accepted at an international level by Taylor & Francis, USA
K. Ramya Laxmi has worked as team lead and senior software developer at InfoTech Pvt Ltd for four years. Presently she is working as associate professor in the CSE Department at the Sreyas Institute of Engineering and Technology, Hyderabad. Her research interests cover the ﬁelds of data mining, machine learning and image processing. She has good academics and research experience in various areas of Computer Science. She has good hands-on-experience in PHP and Python and has knowledge of tools such as Pentaho and Weka, and is apt at analysing statistics using R-Programming.