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3-D Computer Vision : Principles, Algorithms and Applications / / by Yu-Jin Zhang
| 3-D Computer Vision : Principles, Algorithms and Applications / / by Yu-Jin Zhang |
| Autore | Zhang Yu-Jin |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (453 pages) |
| Disciplina | 006.37 |
| Soggetto topico |
Computer vision
Image processing—Digital techniques Image processing Computer science User interfaces (Computer systems) Human-computer interaction Computer Vision Computer Imaging, Vision, Pattern Recognition and Graphics Image Processing Theory and Algorithms for Application Domains Computer Science User Interfaces and Human Computer Interaction Visió per ordinador Processament digital d'imatges |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 981-19-7580-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Introduction -- Chapter 2. Camera Calibration -- Chapter 3. 3-D Image Acquisition -- Chapter 4. Video and Motion Information -- Chapter 5. Moving Object Detection and Tracking -- Chapter 6. Binocular Stereo Vision -- Chapter 7. Monocular Multiple Image Reconstruction -- Chapter 8. Monocular Single Image Reconstruction -- Chapter 9. 3-D Scene Representation -- Chapter 10. Scene Matching -- Chapter 11. Knowledge and Scene Interpretation -- Chapter 12. Spatial-Temporal Behavior Understanding. |
| Record Nr. | UNINA-9910647782503321 |
Zhang Yu-Jin
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / / Shan Liu
| 3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / / Shan Liu |
| Autore | Liu Songbin |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (156 pages) |
| Disciplina | 006.37 |
| Soggetto topico |
Visió per ordinador
Aprenentatge automàtic Machine learning |
| ISBN | 3-030-89180-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910513688503321 |
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Liu Songbin
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / / Shan Liu
| 3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / / Shan Liu |
| Autore | Liu Songbin |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (156 pages) |
| Disciplina | 006.37 |
| Soggetto topico |
Visió per ordinador
Aprenentatge automàtic Machine learning |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-89180-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466555003316 |
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Liu Songbin
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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3D printing in medicine
| 3D printing in medicine |
| Pubbl/distr/stampa | [London, United Kingdom] : , : SpringerOpen, , [2015]- |
| Descrizione fisica | 1 online resource |
| Soggetto topico |
Three-dimensional printing
Medical technology Impressió 3D Medicina Innovacions tecnològiques Visió per ordinador Revistes electròniques Printing, Three-Dimensional |
| Soggetto genere / forma | Periodicals. |
| Soggetto non controllato | Industrial & Management Engineering |
| ISSN | 2365-6271 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Three-dimensional printing in medicine |
| Record Nr. | UNISA-996217618703316 |
| [London, United Kingdom] : , : SpringerOpen, , [2015]- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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3D printing in medicine
| 3D printing in medicine |
| Pubbl/distr/stampa | [London, United Kingdom] : , : SpringerOpen, , [2015]- |
| Descrizione fisica | 1 online resource |
| Soggetto topico |
Three-dimensional printing
Medical technology Impressió 3D Medicina Innovacions tecnològiques Visió per ordinador Revistes electròniques Printing, Three-Dimensional |
| Soggetto genere / forma | Periodicals. |
| ISSN | 2365-6271 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Three-dimensional printing in medicine |
| Record Nr. | UNINA-9910137216603321 |
| [London, United Kingdom] : , : SpringerOpen, , [2015]- | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applications of Medical Artificial Intelligence : First International Workshop, AMAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings / / edited by Shandong Wu, Behrouz Shabestari, Lei Xing
| Applications of Medical Artificial Intelligence : First International Workshop, AMAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings / / edited by Shandong Wu, Behrouz Shabestari, Lei Xing |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (171 pages) |
| Disciplina |
006.3
616.0754 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Application software Artificial intelligence Education - Data processing Social sciences - Data processing Computer Vision Computer and Information Systems Applications Artificial Intelligence Computers and Education Computer Application in Social and Behavioral Sciences Intel·ligència artificial en medicina Diagnòstic per la imatge Visió per ordinador Processament de dades |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN |
9783031177217
3031177215 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Increasing the Accessibility of Peripheral Artery Disease Screening with Deep Learning -- 1 Problem -- 2 Related Work -- 3 Data Collection Study -- 4 System Development -- 5 Validation Study -- 6 Conclusion -- References -- Deep Learning Meets Computational Fluid Dynamics to Assess CAD in CCTA -- 1 Introduction -- 2 Automated Assessment of CAD in CCTA -- 2.1 Straightened Representation of the Coronary Vessels -- 2.2 Representing Ground-Truth Segmentation as a 3D Mesh -- 2.3 Segmentation of Vessels Using U-Nets in Upsampled CTTA -- 2.4 Blood Flow Simulation -- 3 Experimental Validation -- 4 Conclusions and Future Work -- References -- Machine Learning for Dynamically Predicting the Onset of Renal Replacement Therapy in Chronic Kidney Disease Patients Using Claims Data -- 1 Introduction -- 2 Methods -- 2.1 Dataset Description -- 2.2 Task Definition -- 2.3 Data Representation and Processing -- 2.4 Model Description -- 2.5 Model Evaluation -- 3 Experiments and Results -- 3.1 Study Population and Dataset -- 3.2 Model Performance -- 4 Conclusions -- References -- Uncertainty-Aware Geographic Atrophy Progression Prediction from Fundus Autofluorescence -- 1 Introduction -- 2 Method -- 2.1 Data -- 2.2 Model Development -- 2.3 Uncertainty Estimation Using Deep Ensemble -- 3 Results -- 4 Conclusions -- References -- Automated Assessment of Renal Calculi in Serial Computed Tomography Scans -- 1 Introduction -- 1.1 Our Contributions -- 2 Materials and Methods -- 2.1 Data -- 2.2 Calculi Detection and Segmentation -- 2.3 Registration and Stone Matching -- 2.4 Manual Review and Tracking -- 2.5 Evaluation of Performance -- 2.6 Statistical Analysis -- 3 Results -- 3.1 Cohort Characteristics -- 3.2 Performance of the Stone Detection and Segmentation -- 3.3 Performance of Stone Tracking -- 4 Discussion -- References.
Prediction of Mandibular ORN Incidence from 3D Radiation Dose Distribution Maps Using Deep Learning -- 1 Introduction -- 2 Methods and Materials -- 2.1 Data -- 2.2 Prediction Models -- 2.3 Model Evaluation -- 2.4 Statistical Analysis -- 3 Results -- 4 Discussion -- 4.1 ORN Prediction -- 4.2 Study Limitations and Future Work -- 5 Conclusion -- References -- Analysis of Potential Biases on Mammography Datasets for Deep Learning Model Development -- 1 Introduction -- 2 Materials and Methods -- 2.1 Mammography Dataset -- 2.2 Bias Analysis -- 2.3 Bias Correction Techniques -- 2.4 Experimental Setup -- 3 Results and Discussion -- 4 Conclusions -- References -- ECG-ATK-GAN: Robustness Against Adversarial Attacks on ECGs Using Conditional Generative Adversarial Networks -- 1 Introduction -- 2 Methodology -- 2.1 Generator and Discriminator -- 2.2 Objective Function and Individual Losses -- 2.3 Adversarial Attacks -- 3 Experiments -- 3.1 Data Set Preparation -- 3.2 Hyper-parameters -- 3.3 Quantitative Evaluation -- 3.4 Qualitative Evaluation -- 4 Conclusions and Future Work -- References -- CADIA: A Success Story in Breast Cancer Diagnosis with Digital Pathology and AI Image Analysis -- 1 Introduction -- 2 Methods -- 2.1 Starting Point Analysis and Functional Requirement Collection -- 2.2 Sample Selection and Collection -- 2.3 Digital Image Annotation -- 2.4 Model Development -- 2.5 Model Deployment and Integration -- 3 Results -- 4 Conclusions and Future Perspectives -- References -- Was that so Hard? Estimating Human Classification Difficulty -- 1 Introduction -- 2 Estimating Image Difficulty -- 3 Datasets -- 4 Experiments -- 5 Results -- 6 Discussion and Conclusion -- References -- A Deep Learning-Based Interactive Medical Image Segmentation Framework -- 1 Introduction -- 2 Related Work -- 3 Applicative Scope -- 4 Methodology -- 4.1 System. 4.2 Training with Dynamic Data Generation -- 5 Experimental Results -- 5.1 Setup -- 5.2 Automated Evaluation -- 5.3 User Evaluation -- 6 Conclusion -- References -- Deep Neural Network Pruning for Nuclei Instance Segmentation in Hematoxylin and Eosin-Stained Histological Images -- 1 Introduction -- 2 Method -- 2.1 Datasets -- 2.2 Segmentation and Regression Models -- 2.3 Pruning -- 2.4 Merging and Post-processing -- 2.5 Evaluation Metrics -- 3 Results and Discussion -- 4 Conclusion -- References -- Spatial Feature Conservation Networks (SFCNs) for Dilated Convolutions to Improve Breast Cancer Segmentation from DCE-MRI -- 1 Introduction -- 2 Methods -- 2.1 Compensation Module -- 2.2 Network Architecture -- 2.3 Performance Evaluation -- 2.4 Image Dataset and Data Preparation -- 3 Results -- 4 Discussion and Conclusion -- References -- The Impact of Using Voxel-Level Segmentation Metrics on Evaluating Multifocal Prostate Cancer Localisation -- 1 Introduction -- 2 Materials and Methods -- 2.1 Prostate Lesion Segmentation for Procedure Planning -- 2.2 Voxel-Level Segmentation Metrics -- 2.3 Lesion-Level Object Detection Metrics -- 2.4 Lesion Detection Metrics for Multifocal Segmentation Output -- 2.5 Correlation, Pairwise Agreement and Impact on Evaluation -- 3 Results -- 3.1 Comparison Between DSC and HD -- 3.2 Comparison Between Voxel- and Lesion-Level Metrics -- 4 Conclusion -- References -- OOOE: Only-One-Object-Exists Assumption to Find Very Small Objects in Chest Radiographs -- 1 Introduction -- 2 Methods -- 2.1 Feature Extractor -- 2.2 Point Detection Head -- 3 Experiments -- 3.1 Datasets -- 3.2 Evaluation Metrics -- 3.3 Implementation Details -- 3.4 Comparison to Other Methods -- 3.5 A Closer Look at ET-tube vs. T-tube Detection Performance -- 4 Conclusion -- References -- Wavelet Guided 3D Deep Model to Improve Dental Microfracture Detection. 1 Introduction -- 2 Materials -- 3 Methods -- 4 Results and Discussion -- References -- Author Index. |
| Record Nr. | UNINA-9910616210103321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence : 9th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, Puerto de la Cruz, Tenerife, Spain, May 31 – June 3, 2022, Proceedings, Part II / / edited by José Manuel Ferrández Vicente, José Ramón Álvarez-Sánchez, Félix de la Paz López, Hojjat Adeli
| Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence : 9th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, Puerto de la Cruz, Tenerife, Spain, May 31 – June 3, 2022, Proceedings, Part II / / edited by José Manuel Ferrández Vicente, José Ramón Álvarez-Sánchez, Félix de la Paz López, Hojjat Adeli |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (619 p.) |
| Disciplina |
610.28563
006.3 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer science
Computer engineering Computer networks Artificial intelligence Image processing - Digital techniques Computer vision Social sciences - Data processing Theory of Computation Computer Engineering and Networks Artificial Intelligence Computer Imaging, Vision, Pattern Recognition and Graphics Computer Application in Social and Behavioral Sciences Intel·ligència artificial Intel·ligència artificial en medicina Computació evolutiva Aprenentatge automàtic Visió per ordinador |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-06527-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910768465603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Biomedical Image Registration : 10th International Workshop, WBIR 2022, Munich, Germany, July 10–12, 2022, Proceedings / / edited by Alessa Hering, Julia Schnabel, Miaomiao Zhang, Enzo Ferrante, Mattias Heinrich, Daniel Rueckert
| Biomedical Image Registration : 10th International Workshop, WBIR 2022, Munich, Germany, July 10–12, 2022, Proceedings / / edited by Alessa Hering, Julia Schnabel, Miaomiao Zhang, Enzo Ferrante, Mattias Heinrich, Daniel Rueckert |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (223 pages) |
| Disciplina | 006.6 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Machine learning Education - Data processing Social sciences - Data processing Bioinformatics Computer Imaging, Vision, Pattern Recognition and Graphics Machine Learning Computers and Education Computer Application in Social and Behavioral Sciences Computational and Systems Biology Imatges mèdiques Visió per ordinador Aprenentatge automàtic |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-11203-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Atlases -- Topology -- Uncertainty -- Architectures -- Optimization -- Metrics -- Losses -- Efficiency. |
| Record Nr. | UNINA-9910584598603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Cancer Prevention Through Early Detection : First International Workshop, CaPTion 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings / / edited by Sharib Ali, Fons van der Sommen, Bartłomiej Władysław Papież, Maureen van Eijnatten, Yueming Jin, Iris Kolenbrander
| Cancer Prevention Through Early Detection : First International Workshop, CaPTion 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings / / edited by Sharib Ali, Fons van der Sommen, Bartłomiej Władysław Papież, Maureen van Eijnatten, Yueming Jin, Iris Kolenbrander |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (175 pages) |
| Disciplina | 616.0754 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Machine learning Computers Application software Computer Imaging, Vision, Pattern Recognition and Graphics Machine Learning Computing Milieux Computer and Information Systems Applications Diagnòstic per la imatge Càncer Visió per ordinador Processament de dades Aprenentatge automàtic |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031179792
303117979X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Classification -- 3D-Morphomics, Morphological Features on CT Scans for Lung Nodule Malignancy Diagnosis -- 1 Introduction -- 2 Methods -- 2.1 Data Sets -- 2.2 Data Analysis Models -- 3 Results -- 3.1 3D-Morphomics -- 3.2 Lung Nodule Diagnosis Performances of 3D-Morphomics -- 4 Conclusions -- References -- .26em plus .1em minus .1emSelf-supervised Approach for a Fully Assistive Esophageal Surveillance: Quality, Anatomy and Neoplasia Guidance -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Self-supervision Solving Jigsaw Puzzle -- 3.2 Fine-Tuning with Angular Margin Loss -- 4 Experiments and Results -- 4.1 Implementation Details -- 4.2 Data Collection and Evaluation Metrics -- 4.3 Comparison with SOTA Methods -- 4.4 Qualitative Analysis -- 5 Conclusion -- References -- Multi-scale Deformable Transformer for the Classification of Gastric Glands: The IMGL Dataset -- 1 Introduction -- 2 Related Works -- 3 Materials and Methods -- 3.1 IMGL Dataset Description -- 3.2 The Proposed IMGL-VTNet Architecture -- 3.3 Multi-scale Deformable Transformer Encoder -- 4 Experimental Results -- 4.1 A Comparison of State-of-the-Art Methods: IMGL Dataset -- 4.2 Feature Map Scales Analysis -- 4.3 Application of the Proposed Model to Pedestrian Detection -- 5 Conclusion -- References -- Parallel Classification of Cells in Thinprep Cytology Test Image for Cervical Cancer Screening -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Dual Classifiers in Parallel -- 2.3 Intra-class Compactness -- 2.4 Implementation Details -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Classification Performance -- 3.3 Evolving of the Latent Space -- 4 Discussion and Conclusion -- References -- Detection and Diagnosis -- Lightweight Transformer Backbone for Medical Object Detection -- 1 Introduction -- 2 Methodology.
2.1 Overview of Proposed Method -- 2.2 Feature Map Rearrangement and Reconstruction -- 2.3 Lightweight Transformer on Feature Patches -- 3 Experiments and Results -- 3.1 Dataset and Evaluation Metrics -- 3.2 Implementation Details -- 3.3 Experimental Results -- 4 Conclusion -- References -- Contrastive and Attention-Based Multiple Instance Learning for the Prediction of Sentinel Lymph Node Status from Histopathologies of Primary Melanoma Tumours -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Multiple Instance Learning -- 2.3 Proposed Model -- 2.4 Self-supervised Contrastive Learning: -- 3 Experimental Set-Up and Results -- 3.1 Feature Extraction -- 3.2 Experiments -- 4 Discussion -- 5 Conclusions -- References -- Knowledge Distillation with a Class-Aware Loss for Endoscopic Disease Detection -- 1 Introduction -- 2 Related Work -- 3 Materials and Method -- 3.1 Datasets -- 3.2 Proposed Knowledge-Distillation Framework -- 4 Experiments and Results -- 4.1 Experimental Setup and Evaluation Metrics -- 4.2 Results -- 5 Conclusion -- References -- IF3: An Interpretable Feature Fusion Framework for Lesion Risk Assessment Based on Auto-constructed Fuzzy Cognitive Maps -- 1 Introduction -- 2 Methodology -- 2.1 Fuzzy Cognitive Maps -- 2.2 Proposed Framework -- 3 Experiments and Results -- 3.1 Dataset Description and Parameter Settings -- 3.2 Interpretable Example of Risk Assessment Using IF3 -- 3.3 Performance Evaluation of IF3 -- 4 Discussion and Conclusions -- References -- Lesion Characterization -- A CAD System for Real-Time Characterization of Neoplasia in Barrett's Esophagus NBI Videos -- 1 Introduction -- 2 Methods -- 2.1 Data -- 2.2 Network Architecture, Training and Evaluation -- 2.3 Video Analysis Methods -- 3 Experimental Results -- 4 Discussion -- 5 Conclusions -- References. Efficient Out-of-Distribution Detection of Melanoma with Wavelet-Based Normalizing Flows -- 1 Introduction -- 2 Background -- 2.1 Normalizing Flows -- 2.2 Wavelet Flow -- 3 Methods -- 4 Results and Discussion -- 5 Conclusion -- References -- Robust Colorectal Polyp Characterization Using a Hybrid Bayesian Neural Network -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Bayesian Neural Networks -- 2.3 Model Architecture -- 2.4 Evaluation Metrics -- 3 Results -- 3.1 Experimental Setting -- 3.2 Calibration-performance Assessment -- 3.3 Model Performance Comparison -- 3.4 Generalization and Robustness to Over-Fitting Assessment -- 4 Discussion and Conclusion -- References -- Active Data Enrichment by Learning What to Annotate in Digital Pathology -- 1 Introduction -- 2 Methodology -- 2.1 Annotation Protocol -- 2.2 Dataset Enrichment -- 3 Results -- 3.1 Unsupervised Data Enrichment -- 3.2 Supervised Active Data Enrichment -- 4 Conclusion -- References -- Segmentation, Registration, and Image-Guided Intervention -- Comparing Training Strategies Using Multi-Assessor Segmentation Labels for Barrett's Neoplasia Detection -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Set -- 2.2 Segmentation Ground-truth Assembly -- 2.3 Network Architecture -- 2.4 Training Details -- 3 Experiments and Results -- 3.1 Metrics -- 3.2 Results -- 4 Discussion and Conclusions -- References -- Improved Pancreatic Tumor Detection by Utilizing Clinically-Relevant Secondary Features -- 1 Introduction -- 2 Related Work on PDAC Detection -- 3 Methods -- 3.1 Data Collection -- 3.2 Segmentation Model for Classification and Localization -- 3.3 Experiments -- 3.4 Data Preparation and Training Details -- 4 Results and Discussion -- 5 Conclusion -- References -- Strategising Template-Guided Needle Placement for MR-targeted Prostate Biopsy -- 1 Introduction -- 2 Method. 2.1 Patient-specific Prostate MR-derived Biopsy Environment -- 2.2 The MDP Components -- 2.3 Policy Learning -- 3 Experiments -- 4 Results -- 5 Discussion and Conclusion -- References -- Semantic-Aware Registration with Weakly-Supervised Learning -- 1 Introduction -- 2 Method -- 2.1 Structural Constraints -- 2.2 Adaptive Registration -- 3 Experiments -- 3.1 Registration Results -- 4 Conclusion -- References -- Author Index. |
| Record Nr. | UNINA-9910616375303321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computational intelligence methods for super-resolution in image processing applications / / Anand Deshpande, Vania V. Estrela, Navid Razmjooy, editors
| Computational intelligence methods for super-resolution in image processing applications / / Anand Deshpande, Vania V. Estrela, Navid Razmjooy, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (308 pages) |
| Disciplina | 006.37 |
| Soggetto topico |
Computer vision
Visió per ordinador Processament digital d'imatges Intel·ligència computacional |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-67921-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483859703321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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