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Artificial Intelligence and Machine Learning for Digital Pathology [[electronic resource] ] : State-of-the-Art and Future Challenges / / edited by Andreas Holzinger, Randy Goebel, Michael Mengel, Heimo Müller
| Artificial Intelligence and Machine Learning for Digital Pathology [[electronic resource] ] : State-of-the-Art and Future Challenges / / edited by Andreas Holzinger, Randy Goebel, Michael Mengel, Heimo Müller |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xii, 339 pages) |
| Disciplina | 616.07540285 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Database management Application software Computer security Optical data processing Artificial Intelligence Computing Milieux Database Management Computer Applications Systems and Data Security Image Processing and Computer Vision |
| ISBN | 3-030-50402-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Expectations of Artificial Intelligence for Pathology -- Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images -- Supporting the Donation of Health Records to Biobanks for Medical Research -- Survey of XAI in Digital Pathology -- Sample Quality as Basic Prerequisite for Data Quality: A Quality Management System for Biobanks -- Black Box Nature of Deep Learning for Digital Pathology: Beyond Quantitative to Qualitative Algorithmic Performances -- Towards a Better Understanding of the Workflows: Modeling Pathology Processes in View of Future AI Integration -- OBDEX – Open Block Data Exchange System -- Image Processing and Machine Learning Techniques for Diabetic Retinopathy Detection: A Review -- Higher Education Teaching Material on Machine Learning in the Domain of Digital Pathology -- Classification vs Deep Learning in Cancer Degree on Limited Histopathology Datasets -- Biobanks and Biobank-Based Artificial Intelligence (AI) Implementation Through an International Lens -- HistoMapr: An Explainable AI (xAI) Platform for Computational Pathology Solutions -- Extension of the Identity Management System Mainzelliste to Reduce Runtimes for Patient Registration in Large Datasets -- Digital Image Analysis in Pathology Using DNA Stain: Contributions in Cancer Diagnostics and Development of Prognostic and Theranostic Biomarkers -- Assessment and Comparison of Colour Fidelity of Whole slide imaging scanners -- Deep Learning Methods for Mitosis Detection in Breast Cancer Histopathological Images: a Comprehensive Review -- Developments in AI and Machine Learning for Neuroimaging. |
| Record Nr. | UNISA-996418313003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Artificial Intelligence and Machine Learning for Digital Pathology : State-of-the-Art and Future Challenges / / edited by Andreas Holzinger, Randy Goebel, Michael Mengel, Heimo Müller
| Artificial Intelligence and Machine Learning for Digital Pathology : State-of-the-Art and Future Challenges / / edited by Andreas Holzinger, Randy Goebel, Michael Mengel, Heimo Müller |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xii, 339 pages) |
| Disciplina |
616.07540285
616.07 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Database management Application software Computer security Optical data processing Artificial Intelligence Computing Milieux Database Management Computer Applications Systems and Data Security Image Processing and Computer Vision |
| ISBN | 3-030-50402-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Expectations of Artificial Intelligence for Pathology -- Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images -- Supporting the Donation of Health Records to Biobanks for Medical Research -- Survey of XAI in Digital Pathology -- Sample Quality as Basic Prerequisite for Data Quality: A Quality Management System for Biobanks -- Black Box Nature of Deep Learning for Digital Pathology: Beyond Quantitative to Qualitative Algorithmic Performances -- Towards a Better Understanding of the Workflows: Modeling Pathology Processes in View of Future AI Integration -- OBDEX – Open Block Data Exchange System -- Image Processing and Machine Learning Techniques for Diabetic Retinopathy Detection: A Review -- Higher Education Teaching Material on Machine Learning in the Domain of Digital Pathology -- Classification vs Deep Learning in Cancer Degree on Limited Histopathology Datasets -- Biobanks and Biobank-Based Artificial Intelligence (AI) Implementation Through an International Lens -- HistoMapr: An Explainable AI (xAI) Platform for Computational Pathology Solutions -- Extension of the Identity Management System Mainzelliste to Reduce Runtimes for Patient Registration in Large Datasets -- Digital Image Analysis in Pathology Using DNA Stain: Contributions in Cancer Diagnostics and Development of Prognostic and Theranostic Biomarkers -- Assessment and Comparison of Colour Fidelity of Whole slide imaging scanners -- Deep Learning Methods for Mitosis Detection in Breast Cancer Histopathological Images: a Comprehensive Review -- Developments in AI and Machine Learning for Neuroimaging. |
| Record Nr. | UNINA-9910410055503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging / / edited by Kenji Suzuki, Yisong Chen
| Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging / / edited by Kenji Suzuki, Yisong Chen |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XXI, 387 p. 140 illus., 96 illus. in color.) |
| Disciplina | 616.07540285 |
| Collana | Intelligent Systems Reference Library |
| Soggetto topico |
Computational intelligence
Biomedical engineering Artificial intelligence Radiology Computational Intelligence Biomedical Engineering and Bioengineering Artificial Intelligence Imaging / Radiology |
| ISBN | 3-319-68843-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910299891903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors
| Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (201 pages) |
| Disciplina | 616.07540285 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Diagnostic imaging - Data processing |
| ISBN | 3-030-97281-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464536003316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors
| Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (201 pages) |
| Disciplina | 616.07540285 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Diagnostic imaging - Data processing |
| ISBN | 3-030-97281-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910551826103321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Clinical image-based procedures, distributed and collaborative learning, artificial intelligence for combating COVID-19 and secure and privacy-preserving machine learning : 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, proceedings / / Cristina Oyarzun Laura [and three others] editors
| Clinical image-based procedures, distributed and collaborative learning, artificial intelligence for combating COVID-19 and secure and privacy-preserving machine learning : 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, proceedings / / Cristina Oyarzun Laura [and three others] editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (201 pages) |
| Disciplina | 616.07540285 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Diagnostic imaging - Data processing
Artificial intelligence - Medical applications |
| ISBN | 3-030-90874-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Additional Editors -- CLIP Preface -- CLIP Organization -- DCL Preface -- DCL Organization -- LL-COVID-19 Preface -- LL-COVID-19 Organization -- PPML Preface -- PPML Organization -- Contents -- CLIP -- Intestine Segmentation with Small Computational Cost for Diagnosis Assistance of Ileus and Intestinal Obstruction -- 1 Introduction -- 2 Methods -- 2.1 Overview -- 2.2 Distance Map Estimation for Preventing Incorrect Shortcuts -- 2.3 Graph-Based Segmentation and Visualization -- 3 Experimental Results -- 3.1 Experimental Setup -- 3.2 Evaluations -- 4 Discussion -- 5 Conclusions -- References -- Generation of Patient-Specific, Ligamentoskeletal, Finite Element Meshes for Scoliosis Correction Planning -- 1 Introduction -- 2 Methods -- 2.1 Overview -- 2.2 Patient-Specific, Ligamentoskeletal, Finite Element Mesh Generation -- 3 Results -- 3.1 Datasets -- 3.2 Quantitative Results -- 3.3 Qualitative Results -- 4 Conclusion -- References -- Bayesian Graph Neural Networks for EEG-Based Emotion Recognition -- 1 Introduction -- 2 Methods -- 2.1 Bayesian Graph Neural Networks -- 2.2 Sparse Graph Variational Auto-encoder -- 2.3 Algorithm for BGNN -- 3 Experiments -- 3.1 Datasets -- 3.2 Classification Settings -- 3.3 Results -- 4 Discussion -- 4.1 Ablation Study -- 4.2 Latent Communities -- 5 Conclusions -- References -- ViTBIS: Vision Transformer for Biomedical Image Segmentation -- 1 Introduction -- 2 Related Work -- 2.1 Convolutional Neural Network -- 2.2 Attention Mechanism -- 2.3 Transformers -- 2.4 Background -- 3 Method -- 3.1 Dataset -- 3.2 Network Architecture -- 3.3 Residual Connection -- 3.4 Loss Function -- 3.5 Evaluation Metrics -- 3.6 Implementation Details -- 4 Results -- 4.1 Ablation Studies -- 5 Conclusions -- References -- Attention-Guided Pancreatic Duct Segmentation from Abdominal CT Volumes -- 1 Introduction -- 2 Methods.
2.1 Pancreatic Attention-Guide -- 2.2 Multi-scale Aggregation -- 3 Experiments and Results -- 3.1 Dataset and Settings -- 3.2 Segmentation Results and Discussion -- 4 Conclusion -- References -- Development of the Next Generation Hand-Held Doppler with Waveform Phasicity Predictive Capabilities Using Deep Learning -- 1 Introduction -- 1.1 Background -- 1.2 Innovation -- 1.3 Implementation Summary -- 2 Methods -- 2.1 Data Preparation -- 2.2 Model Development -- 2.3 Hardware Platform -- 3 Results -- 3.1 Baseline Validation -- 3.2 Manual Experiment -- 4 Conclusion -- References -- Learning from Mistakes: An Error-Driven Mechanism to Improve Segmentation Performance Based on Expert Feedback -- 1 Introduction -- 2 Data -- 3 Method -- 4 Experiments and Results -- 4.1 Proof of Concept: Recovering Systematic Errors -- 4.2 Clinical Application: Predicting Expert Corrections -- 5 Discussion and Conclusion -- References -- TMJOAI: An Artificial Web-Based Intelligence Tool for Early Diagnosis of the Temporomandibular Joint Osteoarthritis -- 1 Introduction -- 2 Dataset -- 3 Proposed Methods -- 3.1 Feature Selection -- 3.2 Comparison of Multiple Machine Learning Algorithms -- 3.3 Histogram Matching -- 4 Experimental Results -- 4.1 Experiments -- 4.2 Algorithm Comparison Results -- 4.3 Histogram Matching and Mandibular Fossa Features Results -- 4.4 Deployment -- 5 Conclusion -- References -- COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty -- 1 Introduction -- 2 Method -- 2.1 Infection Region Segmentation by ISNet -- 2.2 Scale Uncertainty-Aware Prediction Aggregation -- 3 Experiments and Results -- 3.1 Ablation and Comparative Study of ISNet -- 3.2 Segmentation by Aggregation FCN -- 4 Discussion and Conclusions -- References -- DCL -- Multi-task Federated Learning for Heterogeneous Pancreas Segmentation -- 1 Introduction -- 2 Methods. 2.1 FedAvg -- 2.2 FedProx -- 2.3 Dynamic Task Prioritization -- 2.4 Dynamic Weight Averaging -- 3 Experiments and Results -- 3.1 Datasets -- 3.2 Experimental Details -- 3.3 Results -- 4 Discussion -- 5 Conclusion -- References -- Federated Learning in the Cloud for Analysis of Medical Images - Experience with Open Source Frameworks -- 1 Introduction -- 2 Related Work -- 3 Dataset Used in Evaluation -- 4 Overview of Available Open Source Frameworks for FL -- 4.1 TensorFlow Federated -- 4.2 PySyft -- 4.3 Flower -- 5 Experiment Setup -- 6 Results -- 6.1 Results for EfficientNetB0 Architecture -- 6.2 Results for ResNet50 Architecture -- 7 Conclusion -- References -- On the Fairness of Swarm Learning in Skin Lesion Classification -- 1 Introduction -- 2 Related Works -- 2.1 Collaborative Learning and Their Application on Healthcare -- 2.2 Security and Privacy of Federated Learning -- 2.3 Fairness -- 3 Problem Setting and Methods -- 3.1 Problem Setting -- 3.2 Swarm Learning -- 3.3 Local and Centralized Training -- 3.4 Fairness Definition and Metrics -- 4 Experiment and Results -- 4.1 Dataset -- 4.2 Implementation Details -- 4.3 Biases in Models Trained with Different Strategies -- 5 Discussion and Conclusion -- References -- LL-COVID19 -- Lessons Learned from the Development and Application of Medical Imaging-Based AI Technologies for Combating COVID-19: Why Discuss, What Next -- 1 Introduction -- 2 Data Definition -- 3 Data Availability -- 4 Translational Research -- 5 Summary and Next Steps -- References -- The Role of Pleura and Adipose in Lung Ultrasound AI -- 1 Introduction -- 2 Methodology -- 2.1 SubQ Masking -- 2.2 Data -- 2.3 Architecture -- 2.4 Training Strategy -- 3 Experiments -- 4 Results and Discussions -- 5 Conclusion -- References -- DuCN: Dual-Children Network for Medical Diagnosis and Similar Case Recommendation Towards COVID-19. 1 Introduction -- 2 Method -- 2.1 Proposed Model -- 2.2 Dual-Children Network -- 2.3 Loss Functions -- 3 Experiments and Results -- 3.1 Dataset and Experiments -- 3.2 Results -- 3.3 Ablation Study -- 4 Discussion and Conclusions -- References -- PPML -- Data Imputation and Reconstruction of Distributed Parkinson's Disease Clinical Assessments: A Comparative Evaluation of Two Aggregation Algorithms -- 1 Introduction -- 1.1 Clinical Assessments and Challenges -- 1.2 Contributions -- 2 Related Work -- 3 Methods -- 3.1 Data -- 3.2 Model Setup -- 3.3 Aggregation Algorithms -- 4 Experimental Results -- 4.1 Effect of Number of Missing Modalities During Training -- 4.2 Effect of Number of Missing Values During Evaluation -- 5 Discussion and Conclusion -- References -- Defending Medical Image Diagnostics Against Privacy Attacks Using Generative Methods: Application to Retinal Diagnostics -- 1 Introduction -- 2 Background -- 3 Prior Work -- 4 Methodology -- 4.1 Threat Model -- 4.2 Approach for Data Producer to Defend Privacy -- 4.3 Novel Metric Balancing Utility and Privacy -- 5 Experiments -- 5.1 Dataset -- 5.2 Results -- 6 Discussion and Limitations -- 7 Conclusion -- References -- Author Index. |
| Record Nr. | UNISA-996464421703316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning : 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings / / edited by Cristina Oyarzun Laura, M. Jorge Cardoso, Michal Rosen-Zvi, Georgios Kaissis, Marius George Linguraru, Raj Shekhar, Stefan Wesarg, Marius Erdt, Klaus Drechsler, Yufei Chen, Shadi Albarqouni, Spyridon Bakas, Bennett Landman, Nicola Rieke, Holger Roth, Xiaoxiao Li, Daguang Xu, Maria Gabrani, Ender Konukoglu, Michal Guindy, Daniel Rueckert, Alexander Ziller, Dmitrii Usynin, Jonathan Passerat-Palmbach
| Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning : 10th Workshop, CLIP 2021, Second Workshop, DCL 2021, First Workshop, LL-COVID19 2021, and First Workshop and Tutorial, PPML 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings / / edited by Cristina Oyarzun Laura, M. Jorge Cardoso, Michal Rosen-Zvi, Georgios Kaissis, Marius George Linguraru, Raj Shekhar, Stefan Wesarg, Marius Erdt, Klaus Drechsler, Yufei Chen, Shadi Albarqouni, Spyridon Bakas, Bennett Landman, Nicola Rieke, Holger Roth, Xiaoxiao Li, Daguang Xu, Maria Gabrani, Ender Konukoglu, Michal Guindy, Daniel Rueckert, Alexander Ziller, Dmitrii Usynin, Jonathan Passerat-Palmbach |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (201 pages) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Machine learning Computer networks Social sciences - Data processing Computer Vision Machine Learning Computer Communication Networks Computer Application in Social and Behavioral Sciences |
| ISBN | 3-030-90874-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intestine segmentation with small computational cost for diagnosis assistance of ileus and intestinal obstruction -- Generation of Patient-Specific, Ligamentoskeletal, Finite Element Meshes for Scoliosis Correction Planning -- Bayesian Graph Neural Networks For EEG-based Emotion Recognition -- ViTBIS: Vision Transformer for Biomedical Image Segmentation -- Attention-guided pancreatic duct segmentation from abdominal CT volumes -- Development of the Next Generation Hand-Held Doppler With Waveform Phasicity Predictive Capabilities Using Deep Learning -- Learning from mistakes: an error-driven mechanism to improve segmentation performance based on expert feedback -- TMJOAI: an artificial web-based intelligence tool for early diagnosis of the Temporomandibular Joint Osteoarthritis -- COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty -- Multi-task Federated Learning for Heterogeneous Pancreas Segmentation -- Federated Learning in the Cloud for Analysis of Medical Images- Experience with Open Source Frameworks -- On the Fairness of Swarm Learning in Skin Lesion Classification -- Lessons learned from the development and application of medical imaging-based AI technologies for combating COVID-19: why discuss, what next -- The Role of Pleura and Adipose in Lung Ultrasound AI -- DuCN: Dual-children Network for Medical Diagnosis and Similar Case Recommendation towards COVID-19 -- Data imputation and reconstruction of distributed Parkinson's disease clinical assessments: A comparative evaluation of two aggregation algorithms -- Defending Medical Image Diagnostics against Privacy Attacks using Generative Methods: Application to Retinal Diagnostics. |
| Record Nr. | UNINA-9910508452103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Clinical Image-Based Procedures. Translational Research in Medical Imaging [[electronic resource] ] : 5th International Workshop, CLIP 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester, Klaus Drechsler, Yoshinobu Sato, Marius Erdt, Marius George Linguraru, Cristina Oyarzun Laura
| Clinical Image-Based Procedures. Translational Research in Medical Imaging [[electronic resource] ] : 5th International Workshop, CLIP 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester, Klaus Drechsler, Yoshinobu Sato, Marius Erdt, Marius George Linguraru, Cristina Oyarzun Laura |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (IX, 85 p. 40 illus.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Pattern recognition systems Medical informatics Computer graphics Computer Vision Automated Pattern Recognition Health Informatics Computer Graphics |
| ISBN | 3-319-46472-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Personalized Optimal Planning for the Surgical Correction of Metopic Craniosynostosis -- Validation of an Improved Patient-Specific Mold Design for Registration of In-Vivo MRI and Histology of the Prostate -- Fast, Intuitive, Vision-Based: Performance Metrics for Visual Registration, Instrument Guidance, and Image Fusion -- Uncertainty Quantification of Cochlear Implant Insertion from CT images -- Geodesic Registration for Cervical Cancer Radiotherapy -- Detection of Wrist Fractures in X-Ray Images -- Trajectory Smoothing for Guiding Aortic Valve Delivery with Transapical Access -- Stable Anatomical Structure Tracking for video-bronchoscopy Navigation -- An Automatic Free Fluid Detection for Morrison's-Pouch -- Towards a Statistical Shape-aware Deformable Contour Model for Cranial Nerve Identification. |
| Record Nr. | UNISA-996465670003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Clinical Image-Based Procedures. Translational Research in Medical Imaging : 5th International Workshop, CLIP 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester, Klaus Drechsler, Yoshinobu Sato, Marius Erdt, Marius George Linguraru, Cristina Oyarzun Laura
| Clinical Image-Based Procedures. Translational Research in Medical Imaging : 5th International Workshop, CLIP 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester, Klaus Drechsler, Yoshinobu Sato, Marius Erdt, Marius George Linguraru, Cristina Oyarzun Laura |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (IX, 85 p. 40 illus.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Pattern recognition systems Medical informatics Computer graphics Computer Vision Automated Pattern Recognition Health Informatics Computer Graphics |
| ISBN | 3-319-46472-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Personalized Optimal Planning for the Surgical Correction of Metopic Craniosynostosis -- Validation of an Improved Patient-Specific Mold Design for Registration of In-Vivo MRI and Histology of the Prostate -- Fast, Intuitive, Vision-Based: Performance Metrics for Visual Registration, Instrument Guidance, and Image Fusion -- Uncertainty Quantification of Cochlear Implant Insertion from CT images -- Geodesic Registration for Cervical Cancer Radiotherapy -- Detection of Wrist Fractures in X-Ray Images -- Trajectory Smoothing for Guiding Aortic Valve Delivery with Transapical Access -- Stable Anatomical Structure Tracking for video-bronchoscopy Navigation -- An Automatic Free Fluid Detection for Morrison's-Pouch -- Towards a Statistical Shape-aware Deformable Contour Model for Cranial Nerve Identification. |
| Record Nr. | UNINA-9910484190803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
La comunicazione radiologica : dalle basi al referto multimediale / / by Francesco Schiavon, Riccardo Berletti
| La comunicazione radiologica : dalle basi al referto multimediale / / by Francesco Schiavon, Riccardo Berletti |
| Autore | Schiavon Francesco |
| Edizione | [1st ed. 2009.] |
| Pubbl/distr/stampa | Milano, : Springer Milan, 2009 |
| Descrizione fisica | 1 online resource (128 p.) |
| Disciplina |
616.07540285
616.07572 |
| Altri autori (Persone) | BerlettiRiccardo |
| Soggetto topico |
Medicine
Medical radiology |
| ISBN |
1-282-06852-0
9786612068522 88-470-1108-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Nota di contenuto | Introduzione -- Requisiti di efficacia del referto -- Tecnica radiologica: quali scenari oggi? -- Priorità sanitarie attuali -- Semeiotica radiologica: quali scenari oggi? -- L’informazione clinica per un buon referto -- Indici di gradimento del prescrittore -- Metodologia ragionata del referto -- Principali tipologie di esami e di referti -- Tipologie di referti: il razionale -- Referto e psicologia -- La refertazione della negatività -- Referto e linguistica -- L’errore nella refertazione -- Aspetti medico-legali -- Il referto multimediale: definizione, normativa, vantaggi -- Referto multimediale: stato dell’arte. Conclusioni. |
| Record Nr. | UNINA-9910145966103321 |
Schiavon Francesco
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| Milano, : Springer Milan, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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