Deep Learning in Medical Image Processing and Analysis.

Format:

Book

Author/Creator:

Rabie, Khaled.

Contributor:

Karthik, Chandran.

Chowdhury, Subrata.

Dutta, Pushan Kumar.

Series:

Healthcare Technologies Series

Language:

English

Subjects (All):

Deep learning (Machine learning).

Artificial intelligence.

Physical Description:

1 online resource (460 pages)

Edition:

1st ed.

Place of Publication:

Stevenage : Institution of Engineering & Technology, 2023.

Summary:

This book introduces the fundamentals of deep learning for biomedical image analysis for applications including ophthalmology, cancer detection and heart disease. The book discusses multimedia data analysis algorithms and the principles of feature selection, optimisation and analysis.

Contents:

Contents

About the editors

1. Diagnosing and imaging in oral pathology by use of artificial intelligence and deep learning | Nishath Sayed Abdul, Mahesh Shenoy, Shubhangi Mhaske, Sasidhar Singaraju and G.C. Shivakumar

2. Oral implantology with artificial intelligence and applications of image analysis by deep learning | Hiroj Bagde, Nikhat Fatima, Rahul Shrivastav, Lynn Johnson and Supriya Mishra

3. Review of machine learning algorithms for breast and lung cancer detection | Krishna Pai, Rakhee Kallimani, Sridhar Iyer and Rahul J. Pandya

4. Deep learning for streamlining medical image processing | Sarthak Goel, Ayushi Tiwari and B.K Tripathy

5. Comparative analysis of lumpy skin disease detection using deep learning models | Shikhar Katiyar, Krishna Kumar, E. Ramanujam, K. Suganya Devi and Vadagana Nagendra Naidu

6. Can AI-powered imaging be a replacement for radiologists? | Riddhi Paul, Shreejita Karmakar and Prabuddha Gupta

7. Healthcare multimedia data analysis algorithms tools and techniques | Sathya Raja, V. Vijey Nathan and Deva Priya Sethuraj

8. Empirical mode fusion of MRI-PET images using deep convolutional neural networks | N.V. Maheswar Reddy, G. Suryanarayana, J. Premavani and B. Tejaswi

9. A convolutional neural network for scoring of sleep stages from raw single-channel EEG signals | A. Ravi Raja, Sri Tellakula Ramya, M. Rajalakshmi and Duddukuru Sai Lokesh

10. Fundamentals, limitations, and the prospects of deep learning for biomedical image analysis | T. Chandrakumar, Deepthi Tabitha Bennet and Preethi Samantha Bennet

11. Impact of machine learning and deep learning in medical image analysis | Kirti Rawal, Gaurav Sethi and Gurleen Kaur Walia

12. Systemic review of deep learning techniques for high-dimensional medical image fusion | Nigama Vykari Vajjula, Vinukonda Pavani, Kirti Rawal and Deepika Ghai

13. Qualitative perception of a deep learning model in connection with malaria disease classification | R. Saranya, U. Neeraja, R. Saraswathi Meena and T. Chandrakumar

14. Analysis of preperimetric glaucoma using a deep learning classifier and CNN layer-automated perimetry | Dhinakaran Sakthipriya, Thangavel Chandrakumar, B. Johnson, J. B. Prem Kumar and K. Ajay Karthick

15. Deep learning applications in ophthalmology—computer-aided diagnosis | M. Suguna and Priya Thiagarajan

16. Brain tumor analyses adopting a deep learning classifier based on glioma, meningioma, and pituitary parameters | Dhinakaran Sakthipriya, Thangavel Chandrakumar, S. Hirthick, M. Shyam Sundar and M. Saravana Kumar

17. Deep learning method on X-ray image super-resolution based on residual mode encoder–decoder network | Khan Irfana Begum, G.S. Narayana, Ch. Chulika and Ch. Yashwanth

18. Melanoma skin cancer analysis using convolutional neural networks-based deep learning classification | Balakrishnan Ramprakash, Sankayya Muthuramalingam, S.V. Pragharsitha and T. Poornisha

19. Deep learning applications in ophthalmology and computer-aided diagnostics | Renjith V. Ravi, P.K. Dutta, Sudipta Roy and S.B. Goyal

20. Deep learning for biomedical image analysis in place of fundamentals, limitations, and prospects of deep learning for biomedical image analysis | Renjith V. Ravi, Pushan Kumar Dutta, Pronaya Bhattacharya

Index Generated by AI.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

9781839537943

1839537949

OCLC:

1402818126