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Atlas of Operative Craniofacial Surgery / / by: Mesa, John, Buchman, Steven R., Mackay, Donald R., Losee, Joseph E., Havlik, Robert J.
Atlas of Operative Craniofacial Surgery / / by: Mesa, John, Buchman, Steven R., Mackay, Donald R., Losee, Joseph E., Havlik, Robert J.
Autore Allori Alexander C
Pubbl/distr/stampa New York : , : Thieme Medical Publishers, Inc., , [2019]
Descrizione fisica 1 online resource (534 pages)
Disciplina 617.514
Soggetto topico Skull - Surgery
Face - Surgery
ISBN 1-63853-510-8
1-62623-765-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine generated contents note: -- PART I FUNDAMENTALS1 Fundamental Principles2 Craniofacial Nerve BlocksPART II CRANIAL VAULT AND BONY FACE3 Unicoronal Craniosynostosis Reconstruction: Fronto-orbital Advancement4 Fronto-orbital Advancement for Correction of Metopic Craniosynostosis5 Sagittal Craniosynostosis Reconstruction: Total Cranial Vault Remodeling6 Posterior Cranial Vault Expansion7 Monobloc Frontofacial Advancement: Indications and Technique8 Orbital Box Osteotomy for Orbital Dystopia9 Frontal Sinus Cranialization10 Transfacial Approaches to the Skull BasePART III ORBITAL11 Repair of Orbital Floor Fractures12 Treatment of Naso-orbitoethmoid Fractures13 Medial and Lateral Orbital Wall Fractures14 Canthopexy and CanthoplastyPART IV NOSE15 Cranial Bone Graft Harvest16 Nasal Osteotomies17 Primary Cleft Lip RhinoplastyPART V MAXILLA AND MANDIBLE18 LeFort I Osteotomy19 LeFort II Osteotomy20 LeFort III Osteotomy21 Model Surgery22 Computer-Based Model Surgery23 Bilateral Sagittal Split Osteotomy24 Osseous Genioplasty25 Alloplastic Chin Augmentation26 Midface Suspension: Facial Fractures27 Mandibular Distraction Osteogenesis28 Fibula Osteocutaneous Free Flap for Mandible Reconstruction29 Zygomaticomaxillary Complex RepairPART VI EAR30 Autologous Ear Reconstruction31 Alloplastic Ear Reconstruction32 OtoplastyPART VII CLEFT LIP AND PALATE REPAIR33 Unilateral Cleft Lip Repair34 Bilateral Cleft Lip and Nose Repair35 Cleft Lip Adhesion36 Tongue-Lip Adhesion37 Cleft Palate Repair38 Sphincter Pharyngoplasty39 The Posterior Pharyngeal Flap40 Alveolar Bone Grafting.
Record Nr. UNINA-9910793492103321
Allori Alexander C  
New York : , : Thieme Medical Publishers, Inc., , [2019]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Atlas of Operative Craniofacial Surgery / / by: Mesa, John, Buchman, Steven R., Mackay, Donald R., Losee, Joseph E., Havlik, Robert J.
Atlas of Operative Craniofacial Surgery / / by: Mesa, John, Buchman, Steven R., Mackay, Donald R., Losee, Joseph E., Havlik, Robert J.
Autore Allori Alexander C
Pubbl/distr/stampa New York : , : Thieme Medical Publishers, Inc., , [2019]
Descrizione fisica 1 online resource (534 pages)
Disciplina 617.514
Soggetto topico Skull - Surgery
Face - Surgery
ISBN 1-63853-510-8
1-62623-765-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine generated contents note: -- PART I FUNDAMENTALS1 Fundamental Principles2 Craniofacial Nerve BlocksPART II CRANIAL VAULT AND BONY FACE3 Unicoronal Craniosynostosis Reconstruction: Fronto-orbital Advancement4 Fronto-orbital Advancement for Correction of Metopic Craniosynostosis5 Sagittal Craniosynostosis Reconstruction: Total Cranial Vault Remodeling6 Posterior Cranial Vault Expansion7 Monobloc Frontofacial Advancement: Indications and Technique8 Orbital Box Osteotomy for Orbital Dystopia9 Frontal Sinus Cranialization10 Transfacial Approaches to the Skull BasePART III ORBITAL11 Repair of Orbital Floor Fractures12 Treatment of Naso-orbitoethmoid Fractures13 Medial and Lateral Orbital Wall Fractures14 Canthopexy and CanthoplastyPART IV NOSE15 Cranial Bone Graft Harvest16 Nasal Osteotomies17 Primary Cleft Lip RhinoplastyPART V MAXILLA AND MANDIBLE18 LeFort I Osteotomy19 LeFort II Osteotomy20 LeFort III Osteotomy21 Model Surgery22 Computer-Based Model Surgery23 Bilateral Sagittal Split Osteotomy24 Osseous Genioplasty25 Alloplastic Chin Augmentation26 Midface Suspension: Facial Fractures27 Mandibular Distraction Osteogenesis28 Fibula Osteocutaneous Free Flap for Mandible Reconstruction29 Zygomaticomaxillary Complex RepairPART VI EAR30 Autologous Ear Reconstruction31 Alloplastic Ear Reconstruction32 OtoplastyPART VII CLEFT LIP AND PALATE REPAIR33 Unilateral Cleft Lip Repair34 Bilateral Cleft Lip and Nose Repair35 Cleft Lip Adhesion36 Tongue-Lip Adhesion37 Cleft Palate Repair38 Sphincter Pharyngoplasty39 The Posterior Pharyngeal Flap40 Alveolar Bone Grafting.
Record Nr. UNINA-9910809181003321
Allori Alexander C  
New York : , : Thieme Medical Publishers, Inc., , [2019]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Digital Management of Container Terminal Operations / / by Ning Zhao, Yuan Liu, Weijian Mi, Yifan Shen, Mengjue Xia
Digital Management of Container Terminal Operations / / by Ning Zhao, Yuan Liu, Weijian Mi, Yifan Shen, Mengjue Xia
Autore Zhao Ning
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (XIII, 309 p. 241 illus., 220 illus. in color.)
Disciplina 658.5
Soggetto topico Engineering economics
Engineering economy
Transportation engineering
Traffic engineering
Business logistics
Computational intelligence
Artificial intelligence
Application software
Engineering Economics, Organization, Logistics, Marketing
Transportation Technology and Traffic Engineering
Logistics
Computational Intelligence
Artificial Intelligence
Information Systems Applications (incl. Internet)
ISBN 981-15-2937-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Operation Management in the Container Terminal -- Management of the Vessel Unloading Operations in the Container Terminal -- Management of Container Delivery in the Container Terminal -- Management of Container Collection Operations in the Container Terminal. .
Record Nr. UNINA-9910377820303321
Zhao Ning  
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops : ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, Proceedings
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops : ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, Proceedings
Autore Celebi M. Emre
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (397 pages)
Altri autori (Persone) SalekinSirajus
KimHyunwoo
AlbarqouniShadi
BarataCatarina
HalpernAllan
TschandlPhilipp
CombaliaMarc
LiuYuan
ZamzmiGhada
Collana Lecture Notes in Computer Science Series
ISBN 3-031-47401-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Workshop Editors -- ISIC Preface -- ISIC 2023 Organization -- Care-AI 2023 Preface -- Care-AI 2023 Organization -- MedAGI 2023 Preface -- MedAGI 2023 Organization -- DeCaF 2023 Preface -- DeCaF 2023 Organization -- Contents -- Proceedings of the Eighth International Skin Imaging Collaboration Workshop (ISIC 2023) -- Continual-GEN: Continual Group Ensembling for Domain-agnostic Skin Lesion Classification -- 1 Introduction -- 2 Continual-GEN -- 3 Experiments and Results -- 4 Conclusion -- References -- Communication-Efficient Federated Skin Lesion Classification with Generalizable Dataset Distillation -- 1 Introduction -- 2 Method -- 2.1 Generalizable Dataset Distillation -- 2.2 Distillation Process -- 2.3 Communication-Efficient Federated Learning -- 3 Experiment -- 3.1 Datasets and Evaluation Metrics -- 3.2 Implementation Details -- 3.3 Comparison of State-of-the-Arts -- 3.4 Detailed Analysis -- 4 Conclusion -- References -- AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets -- 1 Introduction -- 2 Methodology -- 2.1 Basic ViT -- 2.2 AViT -- 3 Experiments -- 4 Conclusion -- References -- Test-Time Selection for Robust Skin Lesion Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- Global and Local Explanations for Skin Cancer Diagnosis Using Prototypes -- 1 Introduction -- 2 Proposed Approach -- 2.1 Clustering -- 2.2 Global Prototypes -- 2.3 Local Prototypes -- 2.4 Pruning and Final Classifier -- 2.5 Visual Explanations -- 3 Experimental Setup -- 4 Results -- 5 Conclusions -- References -- Evidence-Driven Differential Diagnosis of Malignant Melanoma -- 1 Introduction -- 2 Method -- 3 Experiments -- 3.1 Data -- 3.2 Experimental Settings -- 4 Results and Discussion -- 5 Conclusion -- References.
Proceedings of the First Clinically-Oriented and Responsible AI for Medical Data Analysis (Care-AI 2023) Workshop -- An Interpretable Machine Learning Model with Deep Learning-Based Imaging Biomarkers for Diagnosis of Alzheimer's Disease -- 1 Introduction -- 2 Methods -- 2.1 Study Population -- 2.2 Data Preprocessing -- 2.3 Explainable Boosting Machine (EBM) -- 2.4 Proposed Extension -- 2.5 Extraction of the DL-Biomarkers -- 3 Experiments -- 3.1 Validation Study -- 3.2 EBM Using DL-Biomarkers -- 3.3 Baseline Methods -- 4 Results -- 4.1 Glo-CNN and ROIs -- 4.2 Comparison Study -- 5 Discussion and Conclusions -- References -- Generating Chinese Radiology Reports from X-Ray Images: A Public Dataset and an X-ray-to-Reports Generation Method -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 3.1 CN-CXR Dataset -- 3.2 CN-RadGraph Dataset -- 4 Method -- 5 Results and Analysis -- 5.1 Pre-processing and Evaluation -- 5.2 Performance and Comparisons -- References -- Gradient Self-alignment in Private Deep Learning -- 1 Introduction -- 2 Background and Related Work -- 3 Methodology -- 3.1 DP-SGD with a Cosine Similarity Filter -- 3.2 DP-SGD with Dimension-Filtered Cosine Similarity Filter -- 4 Experiments and Discussion -- 4.1 Experimental Setup -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Cellular Features Based Interpretable Network for Classifying Cell-Of-Origin from Whole Slide Images for Diffuse Large B-cell Lymphoma Patients -- 1 Introduction -- 2 Methodology -- 2.1 Nuclei Segmentation and Classification -- 2.2 Cellular Feature Extraction -- 2.3 AMIL Model Training -- 2.4 CellFiNet Interpretability -- 2.5 Benchmark Methods -- 3 Experiments and Results -- 3.1 Data -- 3.2 Results -- 4 Interpretability -- 5 Conclusion and Discussion -- References.
Multimodal Learning for Improving Performance and Explainability of Chest X-Ray Classification -- 1 Introduction -- 2 Method -- 2.1 Classification Performance Experiments -- 2.2 Explainability Experiments -- 3 Results -- 3.1 Classification Performance Results -- 3.2 Explainability Results -- 4 Conclusion -- References -- Proceedings of the First International Workshop on Foundation Models for Medical Artificial General Intelligence (MedAGI 2023) -- Cross-Task Attention Network: Improving Multi-task Learning for Medical Imaging Applications -- 1 Introduction -- 2 Methods and Materials -- 2.1 Cross-Task Attention Network (CTAN) -- 2.2 Training Details -- 2.3 Evaluation -- 2.4 Datasets -- 3 Experiments and Results -- 4 Discussion -- References -- Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Segmentation and Boundary Prior Maps -- 3.2 Augmenting Input Images -- 3.3 Model Training with SAM-Augmented Images -- 3.4 Model Deployment with SAM-Augmented Images -- 4 Experiments and Results -- 4.1 Datasets and Setups -- 4.2 Polyp Segmentation on Five Datasets -- 4.3 Cell Segmentation on the MoNuSeg Dataset -- 4.4 Gland Segmentation on the GlaS Dataset -- 5 Conclusions -- References -- Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging -- 1 Introduction -- 2 Related Works -- 2.1 UniverSeg -- 2.2 Prostate MR Segmentation -- 3 Experiments -- 3.1 Datasets -- 3.2 UniverSeg Inference -- 3.3 nnUNet -- 3.4 Empirical Evaluation -- 4 Results -- 4.1 Computational Resource -- 4.2 Segmentation Performance -- 4.3 Conclusion -- References -- GPT4MIA: Utilizing Generative Pre-trained Transformer (GPT-3) as a Plug-and-Play Transductive Model for Medical Image Analysis -- 1 Introduction -- 2 Approach -- 2.1 Theoretical Analyses.
2.2 Prompt Construction -- 2.3 Workflow and Use Cases -- 3 Experiments -- 3.1 On Detecting Prediction Errors -- 3.2 On Improving Classification Accuracy -- 3.3 Ablation Studies -- 4 Discussion and Conclusions -- References -- SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology -- 1 Introduction -- 2 Method -- 2.1 Pathology Encoder -- 2.2 Class Prompts -- 2.3 Optimization -- 3 Experiments -- 3.1 Dataset -- 3.2 Results -- 4 Conclusion -- References -- Multi-task Cooperative Learning via Searching for Flat Minima -- 1 Introduction -- 2 Method -- 2.1 Bi-Level Optimization for Cooperative Two-Task Learning -- 2.2 Finding Flat Minima via Injecting Noise -- 3 Experiments -- 3.1 Dataset -- 3.2 Results on MNIST Dataset -- 3.3 Comparison on REFUGE2018 Dataset -- 3.4 Comparison on HRF-AV Dataset -- 4 Conclusion -- References -- MAP: Domain Generalization via Meta-Learning on Anatomy-Consistent Pseudo-Modalities -- 1 Introduction -- 2 Methods -- 2.1 Problem Definition -- 2.2 Pseudo-modality Synthesis -- 2.3 Meta-learning on Anatomy Consistent Image Space -- 2.4 Structural Correlation Constraints -- 2.5 Experimental Settings -- 3 Results -- 4 Conclusion -- References -- A General Computationally-Efficient 3D Reconstruction Pipeline for Multiple Images with Point Clouds -- 1 Introduction -- 2 Related Works -- 3 Method -- 4 Implementation -- 5 Quantitative Results -- 6 Conclusion and Future Work -- References -- GPC: Generative and General Pathology Image Classifier -- 1 Introduction -- 2 Methodology -- 2.1 Problem Formulation -- 2.2 Network Architecture -- 3 Experiments -- 3.1 Datasets -- 3.2 Comparative Models -- 3.3 Experimental Design -- 3.4 Training Details -- 3.5 Metrics -- 4 Results and Discussion -- 5 Conclusions -- References.
Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ Segmentation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experiments -- 5 Conclusions -- References -- Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification -- 1 Introduction -- 2 Related Works -- 2.1 Concept Bottleneck Models -- 2.2 Large Language Models -- 3 Method -- 3.1 Preliminary -- 3.2 Concept Selection with Visual Activation Score -- 4 Experiments -- 4.1 Experimental Results -- 5 Analysis -- 5.1 Analysis on a Visual Activation Score V(c) -- 5.2 Analysis on Target Image Set X -- 5.3 Qualitative Examples -- 6 Conclusion -- References -- SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation -- 1 Introduction -- 2 Experimental Settings -- 3 Surgical Instruments Segmentation with Prompts -- 4 Robustness Under Data Corruption -- 5 Automatic Surgical Scene Segmentation -- 6 Parameter-Efficient Finetuning with Low-Rank Adaptation -- 7 Conclusion -- References -- Evaluation and Improvement of Segment Anything Model for Interactive Histopathology Image Segmentation -- 1 Introduction -- 2 Method -- 2.1 Overview of Segment Anything Model (SAM) -- 2.2 SAM Fine-Tuning Scenarios -- 2.3 Decoder Architecture Modification -- 3 Experiments -- 3.1 Data Description -- 3.2 Implementation Details -- 4 Results -- 4.1 Zero-Shot Performance -- 4.2 Fine-Tuned SAM Performance -- 4.3 Comparison Between SAM and SOTA Interactive Methods -- 4.4 Modified SAM Decoder Performance -- 5 Conclusion -- References -- Task-Driven Prompt Evolution for Foundation Models -- 1 Introduction -- 1.1 Our Approach -- 1.2 Contributions -- 2 Methodology -- 2.1 Prompt Optimization by Oracle Scoring -- 2.2 Learning to Score -- 3 Experiments and Results -- 3.1 Dataset Description -- 3.2 Segmentation Regressor.
3.3 Prompt Optimization.
Record Nr. UNISA-996565867403316
Celebi M. Emre  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops : ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, Proceedings
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops : ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, Proceedings
Autore Celebi M. Emre
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (397 pages)
Altri autori (Persone) SalekinSirajus
KimHyunwoo
AlbarqouniShadi
BarataCatarina
HalpernAllan
TschandlPhilipp
CombaliaMarc
LiuYuan
ZamzmiGhada
Collana Lecture Notes in Computer Science Series
ISBN 3-031-47401-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Workshop Editors -- ISIC Preface -- ISIC 2023 Organization -- Care-AI 2023 Preface -- Care-AI 2023 Organization -- MedAGI 2023 Preface -- MedAGI 2023 Organization -- DeCaF 2023 Preface -- DeCaF 2023 Organization -- Contents -- Proceedings of the Eighth International Skin Imaging Collaboration Workshop (ISIC 2023) -- Continual-GEN: Continual Group Ensembling for Domain-agnostic Skin Lesion Classification -- 1 Introduction -- 2 Continual-GEN -- 3 Experiments and Results -- 4 Conclusion -- References -- Communication-Efficient Federated Skin Lesion Classification with Generalizable Dataset Distillation -- 1 Introduction -- 2 Method -- 2.1 Generalizable Dataset Distillation -- 2.2 Distillation Process -- 2.3 Communication-Efficient Federated Learning -- 3 Experiment -- 3.1 Datasets and Evaluation Metrics -- 3.2 Implementation Details -- 3.3 Comparison of State-of-the-Arts -- 3.4 Detailed Analysis -- 4 Conclusion -- References -- AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets -- 1 Introduction -- 2 Methodology -- 2.1 Basic ViT -- 2.2 AViT -- 3 Experiments -- 4 Conclusion -- References -- Test-Time Selection for Robust Skin Lesion Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- Global and Local Explanations for Skin Cancer Diagnosis Using Prototypes -- 1 Introduction -- 2 Proposed Approach -- 2.1 Clustering -- 2.2 Global Prototypes -- 2.3 Local Prototypes -- 2.4 Pruning and Final Classifier -- 2.5 Visual Explanations -- 3 Experimental Setup -- 4 Results -- 5 Conclusions -- References -- Evidence-Driven Differential Diagnosis of Malignant Melanoma -- 1 Introduction -- 2 Method -- 3 Experiments -- 3.1 Data -- 3.2 Experimental Settings -- 4 Results and Discussion -- 5 Conclusion -- References.
Proceedings of the First Clinically-Oriented and Responsible AI for Medical Data Analysis (Care-AI 2023) Workshop -- An Interpretable Machine Learning Model with Deep Learning-Based Imaging Biomarkers for Diagnosis of Alzheimer's Disease -- 1 Introduction -- 2 Methods -- 2.1 Study Population -- 2.2 Data Preprocessing -- 2.3 Explainable Boosting Machine (EBM) -- 2.4 Proposed Extension -- 2.5 Extraction of the DL-Biomarkers -- 3 Experiments -- 3.1 Validation Study -- 3.2 EBM Using DL-Biomarkers -- 3.3 Baseline Methods -- 4 Results -- 4.1 Glo-CNN and ROIs -- 4.2 Comparison Study -- 5 Discussion and Conclusions -- References -- Generating Chinese Radiology Reports from X-Ray Images: A Public Dataset and an X-ray-to-Reports Generation Method -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 3.1 CN-CXR Dataset -- 3.2 CN-RadGraph Dataset -- 4 Method -- 5 Results and Analysis -- 5.1 Pre-processing and Evaluation -- 5.2 Performance and Comparisons -- References -- Gradient Self-alignment in Private Deep Learning -- 1 Introduction -- 2 Background and Related Work -- 3 Methodology -- 3.1 DP-SGD with a Cosine Similarity Filter -- 3.2 DP-SGD with Dimension-Filtered Cosine Similarity Filter -- 4 Experiments and Discussion -- 4.1 Experimental Setup -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Cellular Features Based Interpretable Network for Classifying Cell-Of-Origin from Whole Slide Images for Diffuse Large B-cell Lymphoma Patients -- 1 Introduction -- 2 Methodology -- 2.1 Nuclei Segmentation and Classification -- 2.2 Cellular Feature Extraction -- 2.3 AMIL Model Training -- 2.4 CellFiNet Interpretability -- 2.5 Benchmark Methods -- 3 Experiments and Results -- 3.1 Data -- 3.2 Results -- 4 Interpretability -- 5 Conclusion and Discussion -- References.
Multimodal Learning for Improving Performance and Explainability of Chest X-Ray Classification -- 1 Introduction -- 2 Method -- 2.1 Classification Performance Experiments -- 2.2 Explainability Experiments -- 3 Results -- 3.1 Classification Performance Results -- 3.2 Explainability Results -- 4 Conclusion -- References -- Proceedings of the First International Workshop on Foundation Models for Medical Artificial General Intelligence (MedAGI 2023) -- Cross-Task Attention Network: Improving Multi-task Learning for Medical Imaging Applications -- 1 Introduction -- 2 Methods and Materials -- 2.1 Cross-Task Attention Network (CTAN) -- 2.2 Training Details -- 2.3 Evaluation -- 2.4 Datasets -- 3 Experiments and Results -- 4 Discussion -- References -- Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Segmentation and Boundary Prior Maps -- 3.2 Augmenting Input Images -- 3.3 Model Training with SAM-Augmented Images -- 3.4 Model Deployment with SAM-Augmented Images -- 4 Experiments and Results -- 4.1 Datasets and Setups -- 4.2 Polyp Segmentation on Five Datasets -- 4.3 Cell Segmentation on the MoNuSeg Dataset -- 4.4 Gland Segmentation on the GlaS Dataset -- 5 Conclusions -- References -- Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging -- 1 Introduction -- 2 Related Works -- 2.1 UniverSeg -- 2.2 Prostate MR Segmentation -- 3 Experiments -- 3.1 Datasets -- 3.2 UniverSeg Inference -- 3.3 nnUNet -- 3.4 Empirical Evaluation -- 4 Results -- 4.1 Computational Resource -- 4.2 Segmentation Performance -- 4.3 Conclusion -- References -- GPT4MIA: Utilizing Generative Pre-trained Transformer (GPT-3) as a Plug-and-Play Transductive Model for Medical Image Analysis -- 1 Introduction -- 2 Approach -- 2.1 Theoretical Analyses.
2.2 Prompt Construction -- 2.3 Workflow and Use Cases -- 3 Experiments -- 3.1 On Detecting Prediction Errors -- 3.2 On Improving Classification Accuracy -- 3.3 Ablation Studies -- 4 Discussion and Conclusions -- References -- SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology -- 1 Introduction -- 2 Method -- 2.1 Pathology Encoder -- 2.2 Class Prompts -- 2.3 Optimization -- 3 Experiments -- 3.1 Dataset -- 3.2 Results -- 4 Conclusion -- References -- Multi-task Cooperative Learning via Searching for Flat Minima -- 1 Introduction -- 2 Method -- 2.1 Bi-Level Optimization for Cooperative Two-Task Learning -- 2.2 Finding Flat Minima via Injecting Noise -- 3 Experiments -- 3.1 Dataset -- 3.2 Results on MNIST Dataset -- 3.3 Comparison on REFUGE2018 Dataset -- 3.4 Comparison on HRF-AV Dataset -- 4 Conclusion -- References -- MAP: Domain Generalization via Meta-Learning on Anatomy-Consistent Pseudo-Modalities -- 1 Introduction -- 2 Methods -- 2.1 Problem Definition -- 2.2 Pseudo-modality Synthesis -- 2.3 Meta-learning on Anatomy Consistent Image Space -- 2.4 Structural Correlation Constraints -- 2.5 Experimental Settings -- 3 Results -- 4 Conclusion -- References -- A General Computationally-Efficient 3D Reconstruction Pipeline for Multiple Images with Point Clouds -- 1 Introduction -- 2 Related Works -- 3 Method -- 4 Implementation -- 5 Quantitative Results -- 6 Conclusion and Future Work -- References -- GPC: Generative and General Pathology Image Classifier -- 1 Introduction -- 2 Methodology -- 2.1 Problem Formulation -- 2.2 Network Architecture -- 3 Experiments -- 3.1 Datasets -- 3.2 Comparative Models -- 3.3 Experimental Design -- 3.4 Training Details -- 3.5 Metrics -- 4 Results and Discussion -- 5 Conclusions -- References.
Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ Segmentation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experiments -- 5 Conclusions -- References -- Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification -- 1 Introduction -- 2 Related Works -- 2.1 Concept Bottleneck Models -- 2.2 Large Language Models -- 3 Method -- 3.1 Preliminary -- 3.2 Concept Selection with Visual Activation Score -- 4 Experiments -- 4.1 Experimental Results -- 5 Analysis -- 5.1 Analysis on a Visual Activation Score V(c) -- 5.2 Analysis on Target Image Set X -- 5.3 Qualitative Examples -- 6 Conclusion -- References -- SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation -- 1 Introduction -- 2 Experimental Settings -- 3 Surgical Instruments Segmentation with Prompts -- 4 Robustness Under Data Corruption -- 5 Automatic Surgical Scene Segmentation -- 6 Parameter-Efficient Finetuning with Low-Rank Adaptation -- 7 Conclusion -- References -- Evaluation and Improvement of Segment Anything Model for Interactive Histopathology Image Segmentation -- 1 Introduction -- 2 Method -- 2.1 Overview of Segment Anything Model (SAM) -- 2.2 SAM Fine-Tuning Scenarios -- 2.3 Decoder Architecture Modification -- 3 Experiments -- 3.1 Data Description -- 3.2 Implementation Details -- 4 Results -- 4.1 Zero-Shot Performance -- 4.2 Fine-Tuned SAM Performance -- 4.3 Comparison Between SAM and SOTA Interactive Methods -- 4.4 Modified SAM Decoder Performance -- 5 Conclusion -- References -- Task-Driven Prompt Evolution for Foundation Models -- 1 Introduction -- 1.1 Our Approach -- 1.2 Contributions -- 2 Methodology -- 2.1 Prompt Optimization by Oracle Scoring -- 2.2 Learning to Score -- 3 Experiments and Results -- 3.1 Dataset Description -- 3.2 Segmentation Regressor.
3.3 Prompt Optimization.
Record Nr. UNINA-9910767528603321
Celebi M. Emre  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Simulating the use of alternative fuels in a turbofan engine / / Jonathan S. Litt and Jeffrey C. Chin, Yuan Liu
Simulating the use of alternative fuels in a turbofan engine / / Jonathan S. Litt and Jeffrey C. Chin, Yuan Liu
Autore Litt Jonathan S.
Pubbl/distr/stampa Cleveland, Ohio : , : National Aeronautics and Space Administration, Glenn Research Center, , September 2013
Descrizione fisica 1 online resource (13 pages) : illustrations
Collana NASA/TM
Soggetto topico Turbofan engines
Fuel tests
Aircraft fuels
Dynamic response
Performance prediction
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910705296803321
Litt Jonathan S.  
Cleveland, Ohio : , : National Aeronautics and Space Administration, Glenn Research Center, , September 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Smart ports / / Weijian Mi and Yuan Liu
Smart ports / / Weijian Mi and Yuan Liu
Autore Mi Weijian
Pubbl/distr/stampa Singapore : , : Springer, , [2022]
Descrizione fisica 1 online resource (208 pages)
Disciplina 371
Soggetto topico Life sciences
ISBN 981-16-9888-0
981-16-9889-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Contents -- About the Authors -- 1 General Introduction -- 1.1 General Introduction to Smart Port -- 1.2 Smart Port and Revolution of New Technologies -- 1.3 Development History of Smart Port -- 1.4 Current Construction of Smart Port -- 2 Ecology of Smart Port -- 2.1 Ecological Environment of Smart Port -- 2.2 Ecological Features of Smart Port -- 2.2.1 Comprehensive Perception -- 2.2.2 Intelligent Decision-Making -- 2.2.3 Autonomous Handling -- 2.2.4 Whole-Process Participation -- 2.2.5 Continuous Innovation -- 3 Smart Port and Cyber-Physical System -- 3.1 General Introduction to Cyber-Physical System -- 3.1.1 The Concept of the Internet of Things (IOT) -- 3.1.2 Composition and Technical Features of IOT -- 3.1.3 Current Application Fields of IOT -- 3.2 Development of Cyber-Physical System -- 3.3 Applications of Cyber-Physical System in Smart Port -- 3.3.1 Whole-Course Tracking and Ship-Shore Docking of Dangerous Goods -- 3.3.2 Identification Analysis of Industrial Internet in International Multimodal Transportation of Containers -- 3.3.3 Automatic Remote Operation and Control of Quay Cranes -- 3.3.4 Application of 5G Wireless Communication Technology in Smart Port -- Bibliography -- 4 Smart Port and Middle-Office System -- 4.1 General Introduction to Middle Office -- 4.1.1 Service Mode of Middle Office -- 4.1.2 Technical Connotation of Middle Office -- 4.1.3 System and Classification of Middle Office -- 4.2 Development of Middle Office -- 4.2.1 Industry Developing Condition of Middle Office Technology -- 4.2.2 Main Applications of Middle-Office Technology -- 4.3 Applications of Digital Middle Office in Smart Port -- 4.3.1 Significance of the Concept of Middle Office to the Integration of Port Resources -- 4.3.2 Development Foundation of Port Middle-Office System -- 4.3.3 Construction of Port Middle-Office System.
Bibliography -- 5 Smart Port and Blockchain Technology -- 5.1 General Introduction to Blockchain -- 5.1.1 Blockchain Concept -- 5.1.2 Blockchain Types -- 5.1.3 Supporting Technologies of Blockchain -- 5.1.4 The Block of a Blockchain -- 5.1.5 Workflow of Blockchain -- 5.1.6 Features of Blockchain -- 5.2 Development of Blockchain -- 5.2.1 Evolution Path of Blockchain -- 5.2.2 An Overview of Blockchain Development -- 5.3 Typical Applications of Blockchain -- 5.3.1 Blockchain + Financial Services -- 5.3.2 Blockchain + Industry Innovation -- 5.3.3 Blockchain + Port and Shipping -- Bibliography -- 6 Smart Port and Artificial Intelligence -- 6.1 General Introduction of AI -- 6.1.1 Concept of AI -- 6.1.2 Fields of AI -- 6.1.3 Categorization of AI -- 6.1.4 Methods in AI -- 6.2 Development of AI -- 6.3 Applications of AI in Smart Port -- 6.3.1 Intelligent Container Collection -- 6.3.2 Intelligent Stowage -- 6.3.3 Intelligent Ship Control -- Bibliography -- 7 Smart Port and Machine Vision -- 7.1 General Introduction to Machine Vision -- 7.1.1 Camera Vision Technology -- 7.1.2 Light Detection and Ranging Vision Technology -- 7.1.3 Other Vision Technologies -- 7.2 Development of Machine Vision -- 7.2.1 General Introduction to Development of Machine Vision Technology -- 7.2.2 Machine Vision and Smart Traffic -- 7.3 Applications of Machine Vision Technology in Smart Port -- 7.3.1 Early Applications of Machine Vision Technology in Port -- 7.3.2 Typical Applications of Machine Vision in Smart Port -- Bibliography -- 8 Smart Port and Virtual Reality/Augmented Reality Technology -- 8.1 Introduction to Virtual Reality/Augmented Reality -- 8.2 Development of AR/VR Technology -- 8.3 Applications of VR/AR Technology in Smart Port -- 8.3.1 Facility Operation and Business Training in Smart Port -- 8.3.2 3D Visualization Supervision of Smart Ports.
8.3.3 Interactive Simulation of Machinery Equipment in Smart Port -- 8.3.4 AR Technology Serving Smart Port -- Bibliography -- 9 Smart Port and System Simulation/Emulation -- 9.1 Concept of System Simulation -- 9.2 Development of System Simulation -- 9.3 Applications of System Simulation in Smart Port -- 9.4 Applications of Emulation in Smart Port -- 9.4.1 Architecture of the Operation Emulation System of the Container Terminal -- 9.4.2 Case of Ship Loading Emulation of the Container Terminal -- 9.4.3 Optimization of Emulation -- Bibliography -- 10 Smart Port and Digital Monitoring and Diagnosis -- 10.1 Overview of Digital Monitoring and Diagnosis -- 10.1.1 Concept of Equipment Condition Monitoring -- 10.1.2 Concept of Digital Monitoring and Diagnosis -- 10.2 Development of Digital Monitoring and Diagnosis -- 10.2.1 Basic Conditions of Digital Monitoring and Diagnosis of Smart Port -- 10.2.2 Visualization of Equipment Monitoring and Diagnosis -- 10.3 Applications of Digital Monitoring and Diagnosis in Smart Port -- 10.3.1 Real-Time on-line Intelligent Condition Monitoring and Fault Analysis System for Reducer -- 10.3.2 TRUCONNECT Remote Monitoring for Crane -- 10.3.3 Application of on-line Automatic Wire Rope Inspection System on Quay Crane Based on Weak Magnetic Detection Principle -- Bibliography -- 11 Development Trend and Target of Smart Port -- 11.1 Development Trend of Main Hot Technologies -- 11.1.1 Development Trend of IOT -- 11.1.2 Development Trend of Blockchain -- 11.1.3 Development Trend of AI -- 11.2 Development Trend of Smart Port -- 11.3 Development Target of Smart Port.
Record Nr. UNINA-9910743344203321
Mi Weijian  
Singapore : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
User's guide for the commercial modular aero-propulsion system simulation (C-MAPSS) [[electronic resource] /] / Yuan Liu ... [and others]
User's guide for the commercial modular aero-propulsion system simulation (C-MAPSS) [[electronic resource] /] / Yuan Liu ... [and others]
Edizione [Version 2.]
Pubbl/distr/stampa Cleveland, Ohio : , : National Aeronautics and Space Administration, Glenn Research Center, , [2012]
Descrizione fisica 1 online resource (iii, 40 pages) : illustrations (some color)
Altri autori (Persone) LiuYuan
Collana NASA/TM
Soggetto topico Actuators
Turbofan engines
Systems simulation
Propulsion
Control systems design
Human-computer interface
Modularity
Aeronautics
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti User's guide for the commercial modular aero-propulsion system simulation
Record Nr. UNINA-9910701918803321
Cleveland, Ohio : , : National Aeronautics and Space Administration, Glenn Research Center, , [2012]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui