Computational Imaging and Analytics in Biomedical Engineering (eBook, ePUB)
Algorithms and Applications
Redaktion: Babu, T. R. Ganesh; Pattanaik, Balachandra; Saravanakumar, U.
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Computational Imaging and Analytics in Biomedical Engineering (eBook, ePUB)
Algorithms and Applications
Redaktion: Babu, T. R. Ganesh; Pattanaik, Balachandra; Saravanakumar, U.
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Details mathematical and numerical methods for medical images and data. It presents various mathematical modeling techniques, numerical analysis, computational techniques, and applications of machine learning for medical images and informatics. It discusses programming concepts and use of computation techniques.
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- Größe: 26.04MB
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Details mathematical and numerical methods for medical images and data. It presents various mathematical modeling techniques, numerical analysis, computational techniques, and applications of machine learning for medical images and informatics. It discusses programming concepts and use of computation techniques.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Erscheinungstermin: 26. Juli 2024
- Englisch
- ISBN-13: 9781003830221
- Artikelnr.: 70229663
- Verlag: Taylor & Francis
- Erscheinungstermin: 26. Juli 2024
- Englisch
- ISBN-13: 9781003830221
- Artikelnr.: 70229663
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
T. R. Ganesh Babu, PhD, is Professor of Electronics and Communication Engineering at Muthayammal Engineering College (Autonomous), Namakkal, India. He has over 25 years of teaching experience and has published many research papers in international and national journals and conferences as well as books and book chapters on topics such as communication engineering, linear integrated circuits, digital communication, digital image processing, control systems, and FAQs in analog and digital signals. He holds one patent and has filed nine more patents. He is a reviewer for several ournals from Springer, Elsevier, and Inderscience. Dr. Babu received a distinguish faculty award from Venus International Foundation, Chennai, India. U. Saravanakumar, PhD, is Professor and Head of Electronics and Communication Engineering at Muthayammal Engineering College (Autonomous), Namakkal, India. His research interests are in the field of VLSI design, silicon photonics, reconfigurable computing, system on chip, and embedded systems. He published more than 50 research articles in journals and conferences and two books from IGI and Springer. He holds several patents. Dr. Saravanakumar is an editor of Advances in Intelligent Systems and an editorial board member and reviewer for several other journals. Balachandra Pattanaik, PhD, is Professor of Electrical and Computer Engineering at Wollega University, Ethiopia, Africa. He holds over 20 innovation patents issued by the Indian government and several international patent grants in Australia and Germany. He has published engineering books and book chapters as well as many papers in national and international publications. He is an advisor to the IEEE Power and Energy Student Chapter at Bule Hora University in Ethiopia, a senior member of IEEE, and a recipient of a Chartered Engineer Award from the Institution of Engineers of India. He has held many administrative positions, such as Head of Department of Electrical Engineering, Principal, and Anna University Chief Superintendent for university examinations, NSS coordinator, research coordinator, accreditation management representative, editorial board member, and chair/vice chair for conference sessions.
1. Statistical Analysis of Seizure Data to Support Clinical Proceedings 2.
Spatial Preprocessing in Segmentation of Brain MRI Using T1 and T2 Images
3. Comparative Volume Analysis of Pediatric Brain with Adult Brain Using T1
MRI Images 4. Comparison of Region of Interest and Cortical Area Thickness
of Seizure and Hemosiderin-Affected Brain Images 5. Design and Analysis of
Classifier for Atrial Fibrillation and Deep Neural Networks with ECG 6.
Design and Analysis of Efficient Short-Time Fourier Transform-Based Feature
Extraction for Removing EOG Artifacts Using Deep Learning Regression 7.
Machine Learning for Medical Images 8. Innovations in Artificial
Intelligence and Human-Computer Interaction in the Digital Era 9.
Computer-Aided Automatic Detection and Diagnosis of Cervical Cancer by
Using Features Markers 10. A Study on Sentiment Analysis 11. Applications
of Magnetic Resonance Imaging Techniques and Their Advancements 12. A
Hybrid-Clustering Approach for Medical Image Segmentation 13. Approaches
for Analyzing Dental Images with Medical Image Processing with Statistics
14. An Investigation on Diabetes Using Multi-Layer Perceptron 15.
Dermoscopic Implementation and Classification on Melanoma Disease Using
Gradient Boost Classifier 16. Image Processing and Deep Learning Techniques
for Lung Disease Segmentation Using the KNN Classifier 17. Design Detecting
and Classifying Melanoma Skin Cancer Using CNN with K Means Clustering 18.
Detection of Lung Cancer Using Fusion Methods for CT and PET Images 19. A
Framework Promoting Position Trust Evaluation System in Cloud Environment
20. Efficient Machine Learning Techniques for Medical Images
Spatial Preprocessing in Segmentation of Brain MRI Using T1 and T2 Images
3. Comparative Volume Analysis of Pediatric Brain with Adult Brain Using T1
MRI Images 4. Comparison of Region of Interest and Cortical Area Thickness
of Seizure and Hemosiderin-Affected Brain Images 5. Design and Analysis of
Classifier for Atrial Fibrillation and Deep Neural Networks with ECG 6.
Design and Analysis of Efficient Short-Time Fourier Transform-Based Feature
Extraction for Removing EOG Artifacts Using Deep Learning Regression 7.
Machine Learning for Medical Images 8. Innovations in Artificial
Intelligence and Human-Computer Interaction in the Digital Era 9.
Computer-Aided Automatic Detection and Diagnosis of Cervical Cancer by
Using Features Markers 10. A Study on Sentiment Analysis 11. Applications
of Magnetic Resonance Imaging Techniques and Their Advancements 12. A
Hybrid-Clustering Approach for Medical Image Segmentation 13. Approaches
for Analyzing Dental Images with Medical Image Processing with Statistics
14. An Investigation on Diabetes Using Multi-Layer Perceptron 15.
Dermoscopic Implementation and Classification on Melanoma Disease Using
Gradient Boost Classifier 16. Image Processing and Deep Learning Techniques
for Lung Disease Segmentation Using the KNN Classifier 17. Design Detecting
and Classifying Melanoma Skin Cancer Using CNN with K Means Clustering 18.
Detection of Lung Cancer Using Fusion Methods for CT and PET Images 19. A
Framework Promoting Position Trust Evaluation System in Cloud Environment
20. Efficient Machine Learning Techniques for Medical Images
1. Statistical Analysis of Seizure Data to Support Clinical Proceedings 2.
Spatial Preprocessing in Segmentation of Brain MRI Using T1 and T2 Images
3. Comparative Volume Analysis of Pediatric Brain with Adult Brain Using T1
MRI Images 4. Comparison of Region of Interest and Cortical Area Thickness
of Seizure and Hemosiderin-Affected Brain Images 5. Design and Analysis of
Classifier for Atrial Fibrillation and Deep Neural Networks with ECG 6.
Design and Analysis of Efficient Short-Time Fourier Transform-Based Feature
Extraction for Removing EOG Artifacts Using Deep Learning Regression 7.
Machine Learning for Medical Images 8. Innovations in Artificial
Intelligence and Human-Computer Interaction in the Digital Era 9.
Computer-Aided Automatic Detection and Diagnosis of Cervical Cancer by
Using Features Markers 10. A Study on Sentiment Analysis 11. Applications
of Magnetic Resonance Imaging Techniques and Their Advancements 12. A
Hybrid-Clustering Approach for Medical Image Segmentation 13. Approaches
for Analyzing Dental Images with Medical Image Processing with Statistics
14. An Investigation on Diabetes Using Multi-Layer Perceptron 15.
Dermoscopic Implementation and Classification on Melanoma Disease Using
Gradient Boost Classifier 16. Image Processing and Deep Learning Techniques
for Lung Disease Segmentation Using the KNN Classifier 17. Design Detecting
and Classifying Melanoma Skin Cancer Using CNN with K Means Clustering 18.
Detection of Lung Cancer Using Fusion Methods for CT and PET Images 19. A
Framework Promoting Position Trust Evaluation System in Cloud Environment
20. Efficient Machine Learning Techniques for Medical Images
Spatial Preprocessing in Segmentation of Brain MRI Using T1 and T2 Images
3. Comparative Volume Analysis of Pediatric Brain with Adult Brain Using T1
MRI Images 4. Comparison of Region of Interest and Cortical Area Thickness
of Seizure and Hemosiderin-Affected Brain Images 5. Design and Analysis of
Classifier for Atrial Fibrillation and Deep Neural Networks with ECG 6.
Design and Analysis of Efficient Short-Time Fourier Transform-Based Feature
Extraction for Removing EOG Artifacts Using Deep Learning Regression 7.
Machine Learning for Medical Images 8. Innovations in Artificial
Intelligence and Human-Computer Interaction in the Digital Era 9.
Computer-Aided Automatic Detection and Diagnosis of Cervical Cancer by
Using Features Markers 10. A Study on Sentiment Analysis 11. Applications
of Magnetic Resonance Imaging Techniques and Their Advancements 12. A
Hybrid-Clustering Approach for Medical Image Segmentation 13. Approaches
for Analyzing Dental Images with Medical Image Processing with Statistics
14. An Investigation on Diabetes Using Multi-Layer Perceptron 15.
Dermoscopic Implementation and Classification on Melanoma Disease Using
Gradient Boost Classifier 16. Image Processing and Deep Learning Techniques
for Lung Disease Segmentation Using the KNN Classifier 17. Design Detecting
and Classifying Melanoma Skin Cancer Using CNN with K Means Clustering 18.
Detection of Lung Cancer Using Fusion Methods for CT and PET Images 19. A
Framework Promoting Position Trust Evaluation System in Cloud Environment
20. Efficient Machine Learning Techniques for Medical Images