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MARC Lista (tabellare)
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops [[electronic resource] ] : MTSAIL 2023, LEAF 2023, AI4Treat 2023, MMMI 2023, REMIA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8–12, 2023, Proceedings / / edited by Jonghye Woo, Alessa Hering, Wilson Silva, Xiang Li, Huazhu Fu, Xiaofeng Liu, Fangxu Xing, Sanjay Purushotham, Tejas S. Mathai, Pritam Mukherjee, Max De Grauw, Regina Beets Tan, Valentina Corbetta, Elmar Kotter, Mauricio Reyes, Christian F. Baumgartner, Quanzheng Li, Richard Leahy, Bin Dong, Hao Chen, Yuankai Huo, Jinglei Lv, Xinxing Xu, Xiaomeng Li, Dwarikanath Mahapatra, Li Cheng, Caroline Petitjean, Benoît Presles
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops [[electronic resource] ] : MTSAIL 2023, LEAF 2023, AI4Treat 2023, MMMI 2023, REMIA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8–12, 2023, Proceedings / / edited by Jonghye Woo, Alessa Hering, Wilson Silva, Xiang Li, Huazhu Fu, Xiaofeng Liu, Fangxu Xing, Sanjay Purushotham, Tejas S. Mathai, Pritam Mukherjee, Max De Grauw, Regina Beets Tan, Valentina Corbetta, Elmar Kotter, Mauricio Reyes, Christian F. Baumgartner, Quanzheng Li, Richard Leahy, Bin Dong, Hao Chen, Yuankai Huo, Jinglei Lv, Xinxing Xu, Xiaomeng Li, Dwarikanath Mahapatra, Li Cheng, Caroline Petitjean, Benoît Presles
Autore Woo Jonghye
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (394 pages)
Disciplina 616.0754
Altri autori (Persone) HeringAlessa
SilvaWilson
LiXiang
FuHuazhu
LiuXiaofeng
XingFangxu
PurushothamSanjay
MathaiTejas S
MukherjeePritam
Collana Lecture Notes in Computer Science
Soggetto topico Image processing - Digital techniques
Computer vision
Computer Imaging, Vision, Pattern Recognition and Graphics
ISBN 3-031-47425-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Artificial Intelligence -- Computer Vision -- Machine Learning -- Medical Imaging -- Explainability -- Privacy-Preserving Learning -- Federated Learning -- Distributed Learning -- Dermatology -- Skin -- Radiology -- Health Informatics -- Radiomics -- Video -- Time Series Data -- Physiological Data -- Longitudinal Data -- Data Fusion -- Motion Tracking.
Record Nr. UNINA-9910831005403321
Woo Jonghye  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops [[electronic resource] ] : MTSAIL 2023, LEAF 2023, AI4Treat 2023, MMMI 2023, REMIA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8–12, 2023, Proceedings / / edited by Jonghye Woo, Alessa Hering, Wilson Silva, Xiang Li, Huazhu Fu, Xiaofeng Liu, Fangxu Xing, Sanjay Purushotham, Tejas S. Mathai, Pritam Mukherjee, Max De Grauw, Regina Beets Tan, Valentina Corbetta, Elmar Kotter, Mauricio Reyes, Christian F. Baumgartner, Quanzheng Li, Richard Leahy, Bin Dong, Hao Chen, Yuankai Huo, Jinglei Lv, Xinxing Xu, Xiaomeng Li, Dwarikanath Mahapatra, Li Cheng, Caroline Petitjean, Benoît Presles
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops [[electronic resource] ] : MTSAIL 2023, LEAF 2023, AI4Treat 2023, MMMI 2023, REMIA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8–12, 2023, Proceedings / / edited by Jonghye Woo, Alessa Hering, Wilson Silva, Xiang Li, Huazhu Fu, Xiaofeng Liu, Fangxu Xing, Sanjay Purushotham, Tejas S. Mathai, Pritam Mukherjee, Max De Grauw, Regina Beets Tan, Valentina Corbetta, Elmar Kotter, Mauricio Reyes, Christian F. Baumgartner, Quanzheng Li, Richard Leahy, Bin Dong, Hao Chen, Yuankai Huo, Jinglei Lv, Xinxing Xu, Xiaomeng Li, Dwarikanath Mahapatra, Li Cheng, Caroline Petitjean, Benoît Presles
Autore Woo Jonghye
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (394 pages)
Disciplina 616.0754
Altri autori (Persone) HeringAlessa
SilvaWilson
LiXiang
FuHuazhu
LiuXiaofeng
XingFangxu
PurushothamSanjay
MathaiTejas S
MukherjeePritam
Collana Lecture Notes in Computer Science
Soggetto topico Image processing - Digital techniques
Computer vision
Computer Imaging, Vision, Pattern Recognition and Graphics
ISBN 3-031-47425-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Artificial Intelligence -- Computer Vision -- Machine Learning -- Medical Imaging -- Explainability -- Privacy-Preserving Learning -- Federated Learning -- Distributed Learning -- Dermatology -- Skin -- Radiology -- Health Informatics -- Radiomics -- Video -- Time Series Data -- Physiological Data -- Longitudinal Data -- Data Fusion -- Motion Tracking.
Record Nr. UNISA-996585471503316
Woo Jonghye  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Ophthalmic Medical Image Analysis : 11th International Workshop, OMIA 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings / / edited by Antony Bhavna, Hao Chen, Huihui Fang, Huazhu Fu, Cecilia S. Lee
Ophthalmic Medical Image Analysis : 11th International Workshop, OMIA 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings / / edited by Antony Bhavna, Hao Chen, Huihui Fang, Huazhu Fu, Cecilia S. Lee
Autore Bhavna Antony
Edizione [1st ed. 2025.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
Descrizione fisica 1 online resource (178 pages)
Disciplina 006.37
Altri autori (Persone) ChenHao
FangHuihui
FuHuazhu
LeeCecilia S
Collana Lecture Notes in Computer Science
Soggetto topico Computer vision
Artificial intelligence
Pattern recognition systems
Computer networks
Computer Vision
Artificial Intelligence
Automated Pattern Recognition
Computer Communication Networks
ISBN 3-031-73119-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Selective Functional Connectivity between Ocular Dominance Columns in the Primary Visual Cortex -- ETSCL: An Evidence Theory-Based Supervised Contrastive Learning Framework for Multi-modal Glaucoma Grading -- VNR-AV: Structural Post-processing for Retinal Arteries and Veins Segmentation -- Wavelet Deep Learning Network for Objective Retinal Functional Estimation from Multimodal Retinal Imaging -- Inter-Frame Sclera Vessel Rotation Tracking for Toric Intraocular Lens Implantation Navigation -- Data Heterogeneity-aware Personalized Federated Learning for Diagnosis -- MM-UNet: A Mixed MLP Architecture for Improved Ophthalmic Image Segmentation -- Coral-CVDs: A consistent ordinal regression model for cardiovascular diseases grading -- Affordable Deep Learning for Diagnosing Inherited and Common Retinal Diseases via Color Fundus Photography -- Comparative Analysis of Data Augmentation for Retinal OCT Biomarker Segmentation -- Advanced Diabetic Retinopathy Classification: Integrating Pathological Indicators Segmentation and Morphological Feature Analysis -- Masked Image Modelling for Retinal OCT Understanding -- A Dual-Stream Network for Langerhans’ Cells Segmentation in CCM Images -- Formula-Driven Data Augmentation and Partial Retinal Layer Copying for Retinal Layer Segmentation -- Enhancing Community Vision Screening: AI-Driven Retinal Photography for Early Disease Detection and Patient Trust -- Enhancing Large Foundation Models to Identify Fundus Diseases Based on Contrastive Enhanced Low-Rank Adaptation Prompt.
Record Nr. UNINA-9910983306303321
Bhavna Antony  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Ophthalmic medical image analysis : 8th international workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, proceedings / / Huazhu Fu [and four others], editors
Ophthalmic medical image analysis : 8th international workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, proceedings / / Huazhu Fu [and four others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (211 pages)
Disciplina 621.367
Collana Lecture Notes in Computer Science
Soggetto topico Optical data processing
Artificial intelligence
ISBN 3-030-87000-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Adjacent Scale Fusion and Corneal Position Embedding for Corneal Ulcer Segmentation -- 1 Introduction -- 2 Methodology -- 2.1 Adjacent Scale Fusion -- 2.2 Corneal Position Embedding -- 3 Experiment -- 3.1 Dataset -- 3.2 Implementation -- 3.3 Quantitative Results -- 3.4 Qualitative Results -- 4 Conclusion -- References -- Longitudinal Detection of Diabetic Retinopathy Early Severity Grade Changes Using Deep Learning -- 1 Introduction -- 2 Methods -- 2.1 Longitudinal Fusion Schemes -- 2.2 Pre-training -- 3 Dataset -- 4 Experiments and Results -- 5 Discussion -- References -- Intra-operative OCT (iOCT) Image Quality Enhancement: A Super-Resolution Approach Using High Quality iOCT 3D Scans -- 1 Introduction -- 2 Methods -- 2.1 Datasets -- 2.2 Image Quality Assessment -- 2.3 Registration -- 2.4 Data Augmentation -- 2.5 Super Resolution with Cycle Consistency -- 3 Results -- 3.1 Image Quality Assessment -- 3.2 Quantitative Analysis -- 3.3 Qualitative Analysis -- 4 Discussion and Conclusions -- References -- Diabetic Retinopathy Detection Based on Weakly Supervised Object Localization and Knowledge Driven Attribute Mining-10pt -- 1 Introduction -- 2 Method -- 2.1 Attention-Drop-Highlight Layer (ADHL) -- 2.2 NAS-ADHL -- 2.3 Attribute Mining (AM) -- 3 Experimental Results -- 3.1 Settings -- 3.2 Ablation Studies -- 3.3 Comparison with SOTA Methods on Disease Grading -- 3.4 User Study on Lesion Identification -- 4 Conclusion -- References -- FARGO: A Joint Framework for FAZ and RV Segmentation from OCTA Images -- 1 Introduction -- 2 Methodology -- 2.1 The Proposed Architecture -- 3 Experiments -- 3.1 Dataset and Image Preprocessing -- 3.2 Experimental Setting -- 3.3 Results -- 4 Conclusion -- References.
CDLRS: Collaborative Deep Learning Model with Joint Regression and Segmentation for Automatic Fovea Localization -- 1 Introduction -- 2 Materials -- 3 Method -- 4 Experiments and Results -- 5 Conclusion -- References -- U-Net with Hierarchical Bottleneck Attention for Landmark Detection in Fundus Images of the Degenerated Retina -- 1 Introduction -- 2 Methods -- 2.1 Model Architecture -- 2.2 Datasets -- 2.3 Implementation Details -- 3 Experiments and Results -- 3.1 Joint Fovea and OD Detection in the Degenerated Retina -- 3.2 Ablation Study -- 4 Conclusions -- References -- Radial U-Net: Improving DMEK Graft Detachment Segmentation in Radial AS-OCT Scans -- 1 Introduction -- 1.1 Related Work -- 2 Methods and Materials -- 2.1 Data -- 2.2 Models and Experiments -- 2.3 Metrics -- 3 Results -- 4 Discussion -- References -- Guided Adversarial Adaptation Network for Retinal and Choroidal Layer Segmentation -- 1 Introduction -- 2 Proposed Method -- 2.1 Overview -- 2.2 Guided Dual-Encoding -- 2.3 Adversarial Adaptation -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Implementation Details -- 3.3 Evaluation Metrics -- 3.4 Results -- 4 Conclusion -- References -- Juvenile Refractive Power Prediction Based on Corneal Curvature and Axial Length via a Domain Knowledge Embedding Network -- 1 Introduction -- 2 Methodology -- 2.1 Data Collection and Pre-processing -- 2.2 Domain Knowledge Embedding Network (DKE-Net) -- 3 Experimental Results -- 4 Discussion -- 4.1 Main Findings -- 4.2 Strengths and Limitations -- References -- Peripapillary Atrophy Segmentation with Boundary Guidance -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Boundary Guidance Block (BGB) -- 3.2 Loss Function -- 4 Experiment and Results -- 4.1 Dataset and Evaluation -- 4.2 Comparison with State-of-Arts -- 4.3 Ablation Study -- 5 Conclusion -- References.
Are Cardiovascular Risk Scores from Genome and Retinal Image Complementary? A Deep Learning Investigation in a Diabetic Cohort -- 1 Introduction and Motivation -- 2 Related Work -- 3 Materials -- 3.1 Dataset -- 3.2 Outcome Variables: Risk Scores -- 4 Methods -- 4.1 Image Pre-processing -- 4.2 Deep Learning Architecture and Training -- 4.3 Evaluation Metrics -- 4.4 Statistical Significance -- 4.5 Activation Visualization -- 5 Results -- 6 Discussions and Conclusions -- References -- Dual-Branch Attention Network and Atrous Spatial Pyramid Pooling for Diabetic Retinopathy Classification Using Ultra-Widefield Images -- 1 Introduction -- 2 Methodology -- 2.1 Dual-Branch Network -- 2.2 Atrous Spatial Pyramid Pooling Module -- 2.3 Efficient Channel Attention Module and Spatial Attention Module -- 3 Experiments -- 3.1 Dataset and Implementation Details -- 3.2 Experimental Results -- 4 Conclusions -- References -- Self-adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images -- 1 Introduction -- 2 Related Works -- 3 Method -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Implement Details and Evaluation Metrics -- 4.3 Results and Discussion -- 5 Conclusion -- References -- Multi-modality Images Analysis: A Baseline for Glaucoma Grading via Deep Learning -- 1 Introduction -- 2 Methodology -- 2.1 Baselines -- 2.2 Local Information of Optic Disc -- 2.3 Ordinal Regression Strategy -- 3 Experiments and Discussion -- 3.1 Overall Performances -- 4 Conclusion -- References -- Impact of Data Augmentation on Retinal OCT Image Segmentation for  Diabetic Macular Edema Analysis -- 1 Introduction -- 2 Methods -- 2.1 Data Augmentation -- 2.2 Segmentation Network -- 2.3 Comparison of Shallow Network Versus Deep Network -- 3 Evaluation -- 3.1 Dataset and Training Process -- 3.2 Evaluation of Data Augmentation Impact on Segmentation.
4 Discussion -- References -- Representation and Reconstruction of Image-Based Structural Patterns of Glaucomatous Defects Using only Two Latent Variables from a Variational Autoencoder -- 1 Introduction -- 2 Methods -- 2.1 Overview -- 2.2 Macular Ganglion Cell - Inner Plexiform Layer Thickness Map -- 2.3 Variational Autoencoder -- 3 Experimental Methods -- 3.1 VAE Model - Training -- 3.2 VAE Model - Testing -- 4 Results -- 5 Discussion and Conclusion -- References -- Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification -- 1 Introduction -- 2 Proposed Model -- 2.1 Base Models -- 2.2 Meta-learner Model -- 3 Experimental Results -- 3.1 Implementation Details -- 3.2 Benchmark Dataset -- 3.3 Results and Discussions -- 4 Conclusions -- References -- Attention Guided Slit Lamp Image Quality Assessment -- 1 Introduction -- 2 Dataset -- 3 Method -- 3.1 Multi-task Two-Branch Architecture -- 3.2 Trainable Forward Grad-CAM -- 3.3 Attention Decision Module -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Parameter Influence -- 4.3 Comparison with Other Methods -- 5 Conclusion -- References -- Robust Retinal Vessel Segmentation from a Data Augmentation Perspective -- 1 Introduction -- 2 Methodology -- 2.1 Channel-Wise Random Gamma Correction (CWRGC) -- 2.2 Channel-Wise Random Vessel Augmentation (CWRVA) -- 3 Experiments -- 3.1 Experiments Setup -- 3.2 Generalization Across Different Datasets -- 3.3 Robustness to Brightness, Contrast and Saturation -- 4 Conclusion -- References -- Correction to: Impact of Data Augmentation on Retinal OCT Image Segmentation for Diabetic Macular Edema Analysis.
Correction to: Chapter "Impact of Data Augmentation on Retinal OCT Image Segmentation for Diabetic Macular Edema Analysis" in: H. Fu et al. (Eds.): Ophthalmic Medical Image Analysis, LNCS 12970, https://doi.org/10.1007/978-3-030-87000-3_16 -- Author Index.
Record Nr. UNINA-9910502660803321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Ophthalmic medical image analysis : 8th international workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, proceedings / / Huazhu Fu [and four others], editors
Ophthalmic medical image analysis : 8th international workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, proceedings / / Huazhu Fu [and four others], editors
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (211 pages)
Disciplina 621.367
Collana Lecture Notes in Computer Science
Soggetto topico Optical data processing
Artificial intelligence
ISBN 3-030-87000-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Adjacent Scale Fusion and Corneal Position Embedding for Corneal Ulcer Segmentation -- 1 Introduction -- 2 Methodology -- 2.1 Adjacent Scale Fusion -- 2.2 Corneal Position Embedding -- 3 Experiment -- 3.1 Dataset -- 3.2 Implementation -- 3.3 Quantitative Results -- 3.4 Qualitative Results -- 4 Conclusion -- References -- Longitudinal Detection of Diabetic Retinopathy Early Severity Grade Changes Using Deep Learning -- 1 Introduction -- 2 Methods -- 2.1 Longitudinal Fusion Schemes -- 2.2 Pre-training -- 3 Dataset -- 4 Experiments and Results -- 5 Discussion -- References -- Intra-operative OCT (iOCT) Image Quality Enhancement: A Super-Resolution Approach Using High Quality iOCT 3D Scans -- 1 Introduction -- 2 Methods -- 2.1 Datasets -- 2.2 Image Quality Assessment -- 2.3 Registration -- 2.4 Data Augmentation -- 2.5 Super Resolution with Cycle Consistency -- 3 Results -- 3.1 Image Quality Assessment -- 3.2 Quantitative Analysis -- 3.3 Qualitative Analysis -- 4 Discussion and Conclusions -- References -- Diabetic Retinopathy Detection Based on Weakly Supervised Object Localization and Knowledge Driven Attribute Mining-10pt -- 1 Introduction -- 2 Method -- 2.1 Attention-Drop-Highlight Layer (ADHL) -- 2.2 NAS-ADHL -- 2.3 Attribute Mining (AM) -- 3 Experimental Results -- 3.1 Settings -- 3.2 Ablation Studies -- 3.3 Comparison with SOTA Methods on Disease Grading -- 3.4 User Study on Lesion Identification -- 4 Conclusion -- References -- FARGO: A Joint Framework for FAZ and RV Segmentation from OCTA Images -- 1 Introduction -- 2 Methodology -- 2.1 The Proposed Architecture -- 3 Experiments -- 3.1 Dataset and Image Preprocessing -- 3.2 Experimental Setting -- 3.3 Results -- 4 Conclusion -- References.
CDLRS: Collaborative Deep Learning Model with Joint Regression and Segmentation for Automatic Fovea Localization -- 1 Introduction -- 2 Materials -- 3 Method -- 4 Experiments and Results -- 5 Conclusion -- References -- U-Net with Hierarchical Bottleneck Attention for Landmark Detection in Fundus Images of the Degenerated Retina -- 1 Introduction -- 2 Methods -- 2.1 Model Architecture -- 2.2 Datasets -- 2.3 Implementation Details -- 3 Experiments and Results -- 3.1 Joint Fovea and OD Detection in the Degenerated Retina -- 3.2 Ablation Study -- 4 Conclusions -- References -- Radial U-Net: Improving DMEK Graft Detachment Segmentation in Radial AS-OCT Scans -- 1 Introduction -- 1.1 Related Work -- 2 Methods and Materials -- 2.1 Data -- 2.2 Models and Experiments -- 2.3 Metrics -- 3 Results -- 4 Discussion -- References -- Guided Adversarial Adaptation Network for Retinal and Choroidal Layer Segmentation -- 1 Introduction -- 2 Proposed Method -- 2.1 Overview -- 2.2 Guided Dual-Encoding -- 2.3 Adversarial Adaptation -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Implementation Details -- 3.3 Evaluation Metrics -- 3.4 Results -- 4 Conclusion -- References -- Juvenile Refractive Power Prediction Based on Corneal Curvature and Axial Length via a Domain Knowledge Embedding Network -- 1 Introduction -- 2 Methodology -- 2.1 Data Collection and Pre-processing -- 2.2 Domain Knowledge Embedding Network (DKE-Net) -- 3 Experimental Results -- 4 Discussion -- 4.1 Main Findings -- 4.2 Strengths and Limitations -- References -- Peripapillary Atrophy Segmentation with Boundary Guidance -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Boundary Guidance Block (BGB) -- 3.2 Loss Function -- 4 Experiment and Results -- 4.1 Dataset and Evaluation -- 4.2 Comparison with State-of-Arts -- 4.3 Ablation Study -- 5 Conclusion -- References.
Are Cardiovascular Risk Scores from Genome and Retinal Image Complementary? A Deep Learning Investigation in a Diabetic Cohort -- 1 Introduction and Motivation -- 2 Related Work -- 3 Materials -- 3.1 Dataset -- 3.2 Outcome Variables: Risk Scores -- 4 Methods -- 4.1 Image Pre-processing -- 4.2 Deep Learning Architecture and Training -- 4.3 Evaluation Metrics -- 4.4 Statistical Significance -- 4.5 Activation Visualization -- 5 Results -- 6 Discussions and Conclusions -- References -- Dual-Branch Attention Network and Atrous Spatial Pyramid Pooling for Diabetic Retinopathy Classification Using Ultra-Widefield Images -- 1 Introduction -- 2 Methodology -- 2.1 Dual-Branch Network -- 2.2 Atrous Spatial Pyramid Pooling Module -- 2.3 Efficient Channel Attention Module and Spatial Attention Module -- 3 Experiments -- 3.1 Dataset and Implementation Details -- 3.2 Experimental Results -- 4 Conclusions -- References -- Self-adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images -- 1 Introduction -- 2 Related Works -- 3 Method -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Implement Details and Evaluation Metrics -- 4.3 Results and Discussion -- 5 Conclusion -- References -- Multi-modality Images Analysis: A Baseline for Glaucoma Grading via Deep Learning -- 1 Introduction -- 2 Methodology -- 2.1 Baselines -- 2.2 Local Information of Optic Disc -- 2.3 Ordinal Regression Strategy -- 3 Experiments and Discussion -- 3.1 Overall Performances -- 4 Conclusion -- References -- Impact of Data Augmentation on Retinal OCT Image Segmentation for  Diabetic Macular Edema Analysis -- 1 Introduction -- 2 Methods -- 2.1 Data Augmentation -- 2.2 Segmentation Network -- 2.3 Comparison of Shallow Network Versus Deep Network -- 3 Evaluation -- 3.1 Dataset and Training Process -- 3.2 Evaluation of Data Augmentation Impact on Segmentation.
4 Discussion -- References -- Representation and Reconstruction of Image-Based Structural Patterns of Glaucomatous Defects Using only Two Latent Variables from a Variational Autoencoder -- 1 Introduction -- 2 Methods -- 2.1 Overview -- 2.2 Macular Ganglion Cell - Inner Plexiform Layer Thickness Map -- 2.3 Variational Autoencoder -- 3 Experimental Methods -- 3.1 VAE Model - Training -- 3.2 VAE Model - Testing -- 4 Results -- 5 Discussion and Conclusion -- References -- Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification -- 1 Introduction -- 2 Proposed Model -- 2.1 Base Models -- 2.2 Meta-learner Model -- 3 Experimental Results -- 3.1 Implementation Details -- 3.2 Benchmark Dataset -- 3.3 Results and Discussions -- 4 Conclusions -- References -- Attention Guided Slit Lamp Image Quality Assessment -- 1 Introduction -- 2 Dataset -- 3 Method -- 3.1 Multi-task Two-Branch Architecture -- 3.2 Trainable Forward Grad-CAM -- 3.3 Attention Decision Module -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Parameter Influence -- 4.3 Comparison with Other Methods -- 5 Conclusion -- References -- Robust Retinal Vessel Segmentation from a Data Augmentation Perspective -- 1 Introduction -- 2 Methodology -- 2.1 Channel-Wise Random Gamma Correction (CWRGC) -- 2.2 Channel-Wise Random Vessel Augmentation (CWRVA) -- 3 Experiments -- 3.1 Experiments Setup -- 3.2 Generalization Across Different Datasets -- 3.3 Robustness to Brightness, Contrast and Saturation -- 4 Conclusion -- References -- Correction to: Impact of Data Augmentation on Retinal OCT Image Segmentation for Diabetic Macular Edema Analysis.
Correction to: Chapter "Impact of Data Augmentation on Retinal OCT Image Segmentation for Diabetic Macular Edema Analysis" in: H. Fu et al. (Eds.): Ophthalmic Medical Image Analysis, LNCS 12970, https://doi.org/10.1007/978-3-030-87000-3_16 -- Author Index.
Record Nr. UNISA-996464422703316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Ophthalmic medical image analysis : 7th International Workshop, OMIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, proceedings / / Huazhu Fu [and four others] editors
Ophthalmic medical image analysis : 7th International Workshop, OMIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, proceedings / / Huazhu Fu [and four others] editors
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (IX, 218 p.) : 19 illus
Disciplina 616.07
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Pathology - Data processing
Eye - Imaging
ISBN 3-030-63419-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Bio-Inspired Attentive Segmentation of Retinal OCT imaging -- DR detection using Optical Coherence Tomography Angiography (OCTA): a transfer learning approach with robustness analysis -- What is the optimal attribution method for explainable ophthalmic disease classification? -- DeSupGAN: Multi-scale Feature Averaging Generative Adversarial Network for Simultaneous De-blurring and Super-resolution of Retinal Fundus Images -- Encoder-Decoder Networks for Retinal Vessel Segmentation using Large Multi-Scale Patches -- Retinal Image Quality Assessment via Specific Structures Segmentation -- Cascaded Attention Guided Network for Retinal Vessel Segmentation -- Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography -- Automated Detection of Diabetic Retinopathy From Smartphone Fundus Videos -- Optic Disc, Cup and Fovea Detection from Retinal Images using U-Net++ with EfficientNet Encoder -- Multi-level Light U-Net and Atrous Spatial Pyramid Pooling for Optic Disc Segmentation on Fundus Image -- An Interactive Approach to Region of Interest Selection in Cytologic Analysis of Uveal Melanoma Based on Unsupervised Clustering -- Retinal OCT Denoising with Pseudo-Multimodal Fusion Network -- Deep-Learning-Based Estimation of 3D Optic-Nerve-Head Shape from 2D Color Fundus Photographs in Cases of Optic Disc Swelling -- Weakly supervised retinal detachment segmentation using deep feature propagation learning in SD-OCT images -- A framework for the discovery of retinal biomarkers in Optical Coherence Tomography Angiography (OCTA) -- An Automated Aggressive Posterior Retinopathy of Prematurity Diagnosis System by Squeeze and Excitation Hierarchical Bilinear Pooling Network -- Weakly-Supervised Lesion-aware and Consistency Regularization for Retinitis Pigmentosa Detection from Ultra-widefield Images -- A Conditional Generative Adversarial Network-based Method for Eye Fundus Image Quality Enhancement -- Construction of quantitative indexes for cataract surgery evaluation based on deep learning -- Hybrid Deep Learning Gaussian Process for Diabetic Retinopathy Diagnosis and Uncertainty Quantification.
Altri titoli varianti OMIA 2020
Record Nr. UNISA-996418214703316
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Ophthalmic medical image analysis : 7th International Workshop, OMIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, proceedings / / Huazhu Fu [and four others] editors
Ophthalmic medical image analysis : 7th International Workshop, OMIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, proceedings / / Huazhu Fu [and four others] editors
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2021]
Descrizione fisica 1 online resource (IX, 218 p.) : 19 illus
Disciplina 616.07
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Pathology - Data processing
Eye - Imaging
ISBN 3-030-63419-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Bio-Inspired Attentive Segmentation of Retinal OCT imaging -- DR detection using Optical Coherence Tomography Angiography (OCTA): a transfer learning approach with robustness analysis -- What is the optimal attribution method for explainable ophthalmic disease classification? -- DeSupGAN: Multi-scale Feature Averaging Generative Adversarial Network for Simultaneous De-blurring and Super-resolution of Retinal Fundus Images -- Encoder-Decoder Networks for Retinal Vessel Segmentation using Large Multi-Scale Patches -- Retinal Image Quality Assessment via Specific Structures Segmentation -- Cascaded Attention Guided Network for Retinal Vessel Segmentation -- Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography -- Automated Detection of Diabetic Retinopathy From Smartphone Fundus Videos -- Optic Disc, Cup and Fovea Detection from Retinal Images using U-Net++ with EfficientNet Encoder -- Multi-level Light U-Net and Atrous Spatial Pyramid Pooling for Optic Disc Segmentation on Fundus Image -- An Interactive Approach to Region of Interest Selection in Cytologic Analysis of Uveal Melanoma Based on Unsupervised Clustering -- Retinal OCT Denoising with Pseudo-Multimodal Fusion Network -- Deep-Learning-Based Estimation of 3D Optic-Nerve-Head Shape from 2D Color Fundus Photographs in Cases of Optic Disc Swelling -- Weakly supervised retinal detachment segmentation using deep feature propagation learning in SD-OCT images -- A framework for the discovery of retinal biomarkers in Optical Coherence Tomography Angiography (OCTA) -- An Automated Aggressive Posterior Retinopathy of Prematurity Diagnosis System by Squeeze and Excitation Hierarchical Bilinear Pooling Network -- Weakly-Supervised Lesion-aware and Consistency Regularization for Retinitis Pigmentosa Detection from Ultra-widefield Images -- A Conditional Generative Adversarial Network-based Method for Eye Fundus Image Quality Enhancement -- Construction of quantitative indexes for cataract surgery evaluation based on deep learning -- Hybrid Deep Learning Gaussian Process for Diabetic Retinopathy Diagnosis and Uncertainty Quantification.
Altri titoli varianti OMIA 2020
Record Nr. UNINA-9910427670103321
Cham, Switzerland : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Ophthalmic Medical Image Analysis [[electronic resource] ] : 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings / / edited by Huazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
Ophthalmic Medical Image Analysis [[electronic resource] ] : 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings / / edited by Huazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (XI, 192 p. 80 illus., 78 illus. in color.)
Disciplina 617.7
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Artificial intelligence
Computer science—Mathematics
Computer organization
Image Processing and Computer Vision
Artificial Intelligence
Mathematics of Computing
Computer Systems Organization and Communication Networks
ISBN 3-030-32956-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Dictionary Learning Informed Deep Neural Network with Application to OCT Images -- Structure-aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image -- Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography -- An amplified-target loss approach for photoreceptor layer segmentation in pathological OCT scans -- Foveal avascular zone segmentation in clinical routine fluorescein angiographies using multitask learning -- Guided M-Net for High-resolution Biomedical Image Segmentation with Weak Boundaries -- 3D-CNN for Glaucoma Detection using Optical Coherence Tomography -- Semi-supervised Adversarial Learning for Diabetic Retinopathy Screening -- Shape Decomposition of Foveal Pit Morphology using Scan Geometry Corrected OCT -- U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography -- Deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Retinal Images -- Robust Optic Disc Localization by Large Scale Learning -- The Channel Attention based Context Encoder Network for Inner Limiting Membrane Detections -- Fundus Image based Retinal Vessel Segmentation Utilizing A Fast and Accurate Fully Convolutional Network -- Network pruning for OCT image classification -- An improved MPB-CNN segmentation method for edema area and neurosensory retinal detachment in SD-OCT images -- Encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy -- Multi-Discriminator Generative Adversarial Networks for improved thin retinal vessel segmentation -- Fovea Localization in Fundus Photographs by Faster R-CNN with Physiological Prior -- Aggressive Posterior Retinopathy of Prematurity Automated Diagnosis via a Deep Convolutional Network -- Automated Stage Analysis of Retinopathy of Prematurity Using Joint Segmentation and Multi-Instance Learning -- Retinopathy Diagnosis using Semi-supervised Multi-channel Generative Adversarial Network.
Record Nr. UNISA-996466320303316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Ophthalmic Medical Image Analysis : 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings / / edited by Huazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
Ophthalmic Medical Image Analysis : 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings / / edited by Huazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
Edizione [1st ed. 2019.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Descrizione fisica 1 online resource (XI, 192 p. 80 illus., 78 illus. in color.)
Disciplina 617.7
616.07
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Artificial intelligence
Computer science—Mathematics
Computer organization
Image Processing and Computer Vision
Artificial Intelligence
Mathematics of Computing
Computer Systems Organization and Communication Networks
ISBN 3-030-32956-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Dictionary Learning Informed Deep Neural Network with Application to OCT Images -- Structure-aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image -- Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography -- An amplified-target loss approach for photoreceptor layer segmentation in pathological OCT scans -- Foveal avascular zone segmentation in clinical routine fluorescein angiographies using multitask learning -- Guided M-Net for High-resolution Biomedical Image Segmentation with Weak Boundaries -- 3D-CNN for Glaucoma Detection using Optical Coherence Tomography -- Semi-supervised Adversarial Learning for Diabetic Retinopathy Screening -- Shape Decomposition of Foveal Pit Morphology using Scan Geometry Corrected OCT -- U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography -- Deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Retinal Images -- Robust Optic Disc Localization by Large Scale Learning -- The Channel Attention based Context Encoder Network for Inner Limiting Membrane Detections -- Fundus Image based Retinal Vessel Segmentation Utilizing A Fast and Accurate Fully Convolutional Network -- Network pruning for OCT image classification -- An improved MPB-CNN segmentation method for edema area and neurosensory retinal detachment in SD-OCT images -- Encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy -- Multi-Discriminator Generative Adversarial Networks for improved thin retinal vessel segmentation -- Fovea Localization in Fundus Photographs by Faster R-CNN with Physiological Prior -- Aggressive Posterior Retinopathy of Prematurity Automated Diagnosis via a Deep Convolutional Network -- Automated Stage Analysis of Retinopathy of Prematurity Using Joint Segmentation and Multi-Instance Learning -- Retinopathy Diagnosis using Semi-supervised Multi-channel Generative Adversarial Network.
Record Nr. UNINA-9910349273003321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui