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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 Social sciences - Data processing Data protection Computer vision Artificial Intelligence Computing Milieux Database Management Computer Application in Social and Behavioral Sciences Data and Information Security 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 Throughan 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 / / edited by Marc Aubreville, David Zimmerer, Mattias Heinrich
| 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 / / edited by Marc Aubreville, David Zimmerer, Mattias Heinrich |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (201 pages) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Computers Application software Machine learning Computer Imaging, Vision, Pattern Recognition and Graphics Computing Milieux Computer and Information Systems Applications Machine Learning |
| ISBN | 3-030-97281-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface MIDOG 2021 -- Domain Adversarial RetinaNet as a Reference Algorithm for the MItosis DOmainGeneralization Challenge -- Assessing domain adaptation techniques for mitosis detection in multi-scanner breast cancer histopathology images -- Domain-Robust Mitotic Figure Detection with StyleGAN -- Two-step Domain Adaptation for Mitosis Cell Detection in Histopathology Images -- Robust Mitosis Detection Using a Cascade Mask-RCNN Approach With Domain-Specific Residual Cycle-GAN Data Augmentation -- Stain-Robust Mitotic Figure Detection for the Mitosis Domain Generalization Challenge -- MitoDet: Simple and robust mitosis detection -- Multi-source Domain Adaptation Using Gradient Reversal Layer for Mitotic Cell Detection -- Rotation Invariance and Extensive Data Augmentation: a strategy for the Mitosis Domain Generalization (MIDOG) Challenge -- Detecting Mitosis against Domain Shift using a Fused Detector and Deep Ensemble Classi cation Model for MIDOG Challenge -- Domain Adaptive Cascade R-CNN for Mitosis DOmain Generalization (MIDOG) Challenge -- Reducing Domain Shift For Mitosis Detection Using Preprocessing Homogenizers -- Cascade RCNN for MIDOG Challenge -- Sk-Unet Model with Fourier Domain for Mitosis Detection -- Preface MOOD21 -- Self-Supervised 3D Out-of-Distribution Detection via Pseudoanomaly Generation -- Self-Supervised Medical Out-of-Distribution Using U-Net Vision Transformers -- SS3D: Unsupervised Out-of-Distribution Detection and Localization for Medical Volumes -- MetaDetector: Detecting Outliers by Learning to Learn from Self-supervision -- AutoSeg - Steering the Inductive Biases for Automatic Pathology Segmentation -- Preface Learn2Reg 2021 -- Deformable Registration of Brain MR Images via a Hybrid Loss -- Fraunhofer MEVIS Image Registration Solutions for the Learn2Reg 2021 Challenge -- Unsupervised Volumetric Displacement Fields Using Cost Function Unrolling -- Conditional Deep Laplacian Pyramid Image Registration Network in Learn2Reg Challenge -- TheLearn2Reg 2021 MICCAI Grand Challenge (PIMed Team) -- Fast 3D registration with accurate optimisation and little learning for Learn2Reg 2021 -- Progressive and Coarse-to-fine Network for Medical Image Registration across Phases, Modalities and Patients. -Semi-supervised Multilevel Symmetric Image Registration Method for Magnetic Resonance Whole Brain Images. . |
| Record Nr. | UNINA-9910551826103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Cancer Prevention, Detection, and Intervention : Third MICCAI Workshop, CaPTion 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings / / edited by Sharib Ali, Fons van der Sommen, Bartłomiej Władysław Papież, Noha Ghatwary, Yueming Jin, Iris Kolenbrander
| Cancer Prevention, Detection, and Intervention : Third MICCAI Workshop, CaPTion 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings / / edited by Sharib Ali, Fons van der Sommen, Bartłomiej Władysław Papież, Noha Ghatwary, Yueming Jin, Iris Kolenbrander |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (251 pages) |
| Disciplina | 616.07540285 |
| 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 |
| ISBN | 3-031-73376-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Classification and characterization -- Multi-center ovarian tumor classification using hierarchical transformer-based multiple-instance learning -- FoTNet Enables Preoperative Differentiation of Malignant Brain Tumors with Deep Learning -- Classification of Endoscopy and Video Capsule Images using Hybrid Model -- Multimodal Deep Learning-based Prediction of Immune Checkpoint Inhibitor Efficacy in Brain Metastases -- Seeing More with Less: Meta-Learning and Diffusion Models for Tumor Characterization in Low-data Settings -- Performance Evaluation of Deep Learning and Transformer Models Using Multimodal Data for Breast Cancer Classification -- Detection and Segmentation -- On undesired emergent behaviors in compound prostate cancer detection systems -- Optimizing Multi-Expert Consensus for Classification and Precise Localization of Barrett’s Neoplasia -- Automated Hepatocellular Carcinoma Analysis in Multi-Phase CT with Deep Learning -- Refining deep learning segmentation maps with a local thresholding approach: application to liver surface nodularity quantification in CT -- Uncertainty-Aware Deep Learning Classification for MRI-based Prostate Cancer Detection -- Generalized Polyp Detection from Colonoscopy frames Using proposed EDF-YOLO8 Network -- AI-Assisted Laryngeal Examination System -- UltraWeak: Enhancing Breast Ultrasound Cancer Detection with Deformable DETR and Weak Supervision -- SelectiveKD: A semi-supervised framework for cancer detection in DBT through Knowledge Distillation and Pseudo-labeling -- Cancer/Early cancer detection, treatment, and survival prognosis.-AI Age Discrepancy: A Novel Parameter for Frailty Assessment in Kidney Tumor Patients -- Deep Neural Networks for Predicting Recurrence and Survival in Patients with Esophageal Cancer After Surgery -- Treatment efficacy prediction of focused ultrasound therapies using multi-parametric magnetic resonance imaging -- SurRecNet: A Multi-Task Model with Integrating MRI and Diagnostic Descriptions for Rectal Cancer Survival Analysis -- Improved prediction of recurrence after prostate cancer radiotherapy using multimodal data and in silico simulations -- AutoDoseRank: Automated Dosimetry-informed Segmentation Ranking for Radiotherapy -- SurvCORN: Survival Analysis with Conditional Ordinal Ranking Neural Network. |
| Record Nr. | UNINA-9910983342203321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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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 | ||
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