State of the Art in Neural Networks and Their Applications: Volume 2
Editat de Jasjit Suri, Ayman S. El-Bazen Limba Engleză Paperback – dec 2022
State of the Art in Neural Networks and Their Applications is presented in two volumes. Volume One: Neural Networks in Oncology Imaging covers lung cancer, prostate cancer, and bladder cancer. Volume Two: Neural Networks in Brain Disorders and Other Diseases covers autism spectrum disorder, Alzheimer’s disease, attention deficit hyperactivity disorder, hypertension, and other diseases. Written by experienced engineers in the field, these two volumes will help engineers, computer scientists, researchers, and clinicians understand the technology and applications of artificial neural networks.
- Includes applications of neural networks, AI, machine learning, and deep learning techniques to a variety of oncology imaging technologies
- Provides in-depth technical coverage of computer-aided diagnosis (CAD), including coverage of computer-aided classification, unified deep learning frameworks, 3D MRI, PET/CT, and more
- Covers deep learning cancer identification from histopathological images, medical image analysis, detection, segmentation and classification via AI
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (2) | 1154.81 lei 6-8 săpt. | |
ELSEVIER SCIENCE – 25 iul 2021 | 1154.81 lei 6-8 săpt. | |
ELSEVIER SCIENCE – dec 2022 | 1155.01 lei 6-8 săpt. |
Preț: 1155.01 lei
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Specificații
ISBN-13: 9780128198728
ISBN-10: 0128198729
Pagini: 326
Dimensiuni: 191 x 235 x 23 mm
Greutate: 0.57 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0128198729
Pagini: 326
Dimensiuni: 191 x 235 x 23 mm
Greutate: 0.57 kg
Editura: ELSEVIER SCIENCE
Public țintă
Biomedical engineers and researchers in neural engineering, medical imaging, and neural networks and students, researchers, and clinicians in oncology and related fieldsCuprins
1. Microscopy Cancer Cell Imaging in B-Lineage Acute Lymphoblastic Leukemia
2. Computational Applications in Brain and Breast Cancer
3. Deep Neural Networks and Advanced Computer Vision Algorithms in The Early Diagnosis of Skin Diseases
4. An Accurate Deep Learning-Based CAD System For Early Diagnosis Of Prostate Cancer
5. Adaptive Graph Convolutional Neural Network and its Biomedical Applications
6. Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
7. New Explainable Deep CNN Design for Classifying Breast Tumor Response over Neoadjuvant Chemotherapy
8. Deep Learning Interpretability: Measuring The Relevance of Clinical Concepts in CNN Features
9. Computational Lung Sound Classification: A Review
10. Clinical Applications of Machine Learning in Heart Failure
11. Role of AI and Radiomics in Diagnosing Renal Tumors: A Survey
12. Texture-Centric Diagnostic Models for Thyroid-Cancer Using Convolutional Neural Networks: Bridging the Gap Between Radiomics and Microscopic Domains
2. Computational Applications in Brain and Breast Cancer
3. Deep Neural Networks and Advanced Computer Vision Algorithms in The Early Diagnosis of Skin Diseases
4. An Accurate Deep Learning-Based CAD System For Early Diagnosis Of Prostate Cancer
5. Adaptive Graph Convolutional Neural Network and its Biomedical Applications
6. Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
7. New Explainable Deep CNN Design for Classifying Breast Tumor Response over Neoadjuvant Chemotherapy
8. Deep Learning Interpretability: Measuring The Relevance of Clinical Concepts in CNN Features
9. Computational Lung Sound Classification: A Review
10. Clinical Applications of Machine Learning in Heart Failure
11. Role of AI and Radiomics in Diagnosing Renal Tumors: A Survey
12. Texture-Centric Diagnostic Models for Thyroid-Cancer Using Convolutional Neural Networks: Bridging the Gap Between Radiomics and Microscopic Domains