Handbook of Deep Learning in Biomedical Engineering and Health Informatics
Herausgeber: Julie, E Golden; Jaisakthi, S M; Robinson, Y Harold
Handbook of Deep Learning in Biomedical Engineering and Health Informatics
Herausgeber: Julie, E Golden; Jaisakthi, S M; Robinson, Y Harold
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This volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. It delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis.
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This volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. It delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis.
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 318
- Erscheinungstermin: 22. September 2021
- Englisch
- Abmessung: 234mm x 156mm x 21mm
- Gewicht: 658g
- ISBN-13: 9781771889988
- ISBN-10: 1771889985
- Artikelnr.: 62231603
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 318
- Erscheinungstermin: 22. September 2021
- Englisch
- Abmessung: 234mm x 156mm x 21mm
- Gewicht: 658g
- ISBN-13: 9781771889988
- ISBN-10: 1771889985
- Artikelnr.: 62231603
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
E. Golden Julie, PhD, is a Senior Assistant Professor in the Department of Computer Science and Engineering at Anna University, Regional Campus, Tirunelveli, India. With more than¿ 12 ¿years¿ of¿ experience ¿in ¿teaching, she has¿ published¿ and presented many papers at national and international conferences. She ¿has¿ written¿ ten book chapters and is co-editor of the books Successful Implementation and Deployment of IoT Projects in Smart Cities and Handbook of Research on Blockchain Technology: Trend and Technologies. She also acts as a reviewer for many journals on computers and electrical engineering. Y. Harold Robinson, PhD, is currently working at the School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. He¿ has¿ more¿ than ¿15 ¿years¿ of¿ experience ¿in ¿teaching, has published¿ many papers in international¿ journals and presented ¿at¿ both ¿national ¿and ¿international¿ conferences.¿ Along with Dr. Julie, Dr. Robinson is co-editor of the books Successful Implementation and Deployment of IoT Projects in Smart Cities and Handbook of Research on Blockchain Technology: Trend and Technologies. He ¿is ¿a reviewer¿ of¿ many journals. S. M. Jaisakthi, PhD, is an Associate Professor at the School of Computer Science and Engineering at the Vellore Institute of Technology, Vellore, India. Dr. Jaisakthi has extensive research experience in machine learning in image processing, medical image analysis and in building deep learning models. She has published many research publications in refereed international journals and in proceedings of international conferences. Currently she is investigating a project funded by the Science and Engineering Research Board (SERB).
1. Review of Existing Systems in Biomedical Using Deep Learning Algorithms
2. An Overview of Convolutional Neural Network Architecture and Its
Variants in Medical Diagnostics of Cancer and COVID-19 3. Technical
Assessment of Various Image Stitching Techniques: A Deep Learning Approach
4. CCNN: A Deep Learning Approach for an Acute Neurocutaneous Syndrome via
Cloud-Based MRI Images 5. Critical Investigation and Prototype Study on
Deep Brain Stimulations: An Application of Biomedical Engineering in
Healthcare 6. Insight into Various Algorithms for Medical Image Analyzes
Using Convolutional Neural Networks (Deep Learning) 7. Exploration of Deep
RNN Architectures: LSTM and GRU in Medical Diagnostics of Cardiovascular
and Neuro Diseases 8. Medical Image Classification and Manifold Disease
Identification Through Convolutional Neural Networks: A Research
Perspective 9. Melanoma Detection on Skin Lesion Images Using K-Means
Algorithm and SVM Classifier 10. Role of Deep Learning Techniques in
Detecting Skin Cancer: A Review 11. Deep Learning and Its Applications in
Biomedical Image Processing
2. An Overview of Convolutional Neural Network Architecture and Its
Variants in Medical Diagnostics of Cancer and COVID-19 3. Technical
Assessment of Various Image Stitching Techniques: A Deep Learning Approach
4. CCNN: A Deep Learning Approach for an Acute Neurocutaneous Syndrome via
Cloud-Based MRI Images 5. Critical Investigation and Prototype Study on
Deep Brain Stimulations: An Application of Biomedical Engineering in
Healthcare 6. Insight into Various Algorithms for Medical Image Analyzes
Using Convolutional Neural Networks (Deep Learning) 7. Exploration of Deep
RNN Architectures: LSTM and GRU in Medical Diagnostics of Cardiovascular
and Neuro Diseases 8. Medical Image Classification and Manifold Disease
Identification Through Convolutional Neural Networks: A Research
Perspective 9. Melanoma Detection on Skin Lesion Images Using K-Means
Algorithm and SVM Classifier 10. Role of Deep Learning Techniques in
Detecting Skin Cancer: A Review 11. Deep Learning and Its Applications in
Biomedical Image Processing
1. Review of Existing Systems in Biomedical Using Deep Learning Algorithms
2. An Overview of Convolutional Neural Network Architecture and Its
Variants in Medical Diagnostics of Cancer and COVID-19 3. Technical
Assessment of Various Image Stitching Techniques: A Deep Learning Approach
4. CCNN: A Deep Learning Approach for an Acute Neurocutaneous Syndrome via
Cloud-Based MRI Images 5. Critical Investigation and Prototype Study on
Deep Brain Stimulations: An Application of Biomedical Engineering in
Healthcare 6. Insight into Various Algorithms for Medical Image Analyzes
Using Convolutional Neural Networks (Deep Learning) 7. Exploration of Deep
RNN Architectures: LSTM and GRU in Medical Diagnostics of Cardiovascular
and Neuro Diseases 8. Medical Image Classification and Manifold Disease
Identification Through Convolutional Neural Networks: A Research
Perspective 9. Melanoma Detection on Skin Lesion Images Using K-Means
Algorithm and SVM Classifier 10. Role of Deep Learning Techniques in
Detecting Skin Cancer: A Review 11. Deep Learning and Its Applications in
Biomedical Image Processing
2. An Overview of Convolutional Neural Network Architecture and Its
Variants in Medical Diagnostics of Cancer and COVID-19 3. Technical
Assessment of Various Image Stitching Techniques: A Deep Learning Approach
4. CCNN: A Deep Learning Approach for an Acute Neurocutaneous Syndrome via
Cloud-Based MRI Images 5. Critical Investigation and Prototype Study on
Deep Brain Stimulations: An Application of Biomedical Engineering in
Healthcare 6. Insight into Various Algorithms for Medical Image Analyzes
Using Convolutional Neural Networks (Deep Learning) 7. Exploration of Deep
RNN Architectures: LSTM and GRU in Medical Diagnostics of Cardiovascular
and Neuro Diseases 8. Medical Image Classification and Manifold Disease
Identification Through Convolutional Neural Networks: A Research
Perspective 9. Melanoma Detection on Skin Lesion Images Using K-Means
Algorithm and SVM Classifier 10. Role of Deep Learning Techniques in
Detecting Skin Cancer: A Review 11. Deep Learning and Its Applications in
Biomedical Image Processing