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Domain Adaptation and Representation Transfer [[electronic resource] ] : 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings / / edited by Lisa Koch, M. Jorge Cardoso, Enzo Ferrante, Konstantinos Kamnitsas, Mobarakol Islam, Meirui Jiang, Nicola Rieke, Sotirios A. Tsaftaris, Dong Yang
| Domain Adaptation and Representation Transfer [[electronic resource] ] : 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings / / edited by Lisa Koch, M. Jorge Cardoso, Enzo Ferrante, Konstantinos Kamnitsas, Mobarakol Islam, Meirui Jiang, Nicola Rieke, Sotirios A. Tsaftaris, Dong Yang |
| Autore | Koch Lisa |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (180 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
CardosoM. Jorge
FerranteEnzo KamnitsasKonstantinos IslamMobarakol JiangMeirui RiekeNicola TsaftarisSotirios A YangDong |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Application software Machine learning Computers Information technology - Management Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications Machine Learning Computing Milieux Computer Application in Administrative Data Processing |
| ISBN | 3-031-45857-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Domain adaptation of MRI scanners as an alternative to MRI harmonization -- MultiVT: Multiple-Task Framework for Dentistry -- Black-Box Unsupervised Domain Adaptation for Medical Image Segmentation -- PLST: A Pseudo-Labels with a Smooth Transition Strategy for Medical Site Adaptation -- Compositional Representation Learning for Brain Tumor Segmentation -- Hierarchical Compositionality in Hyperbolic Space for Robust Medical Image Segmentation -- Realistic Data Enrichment for Robust Image Segmentation in Kidney Transplant Pathology -- Boosting Knowledge Distillation via Random Fourier Features for Prostate Cancer Grading in Histopathology Images -- Semi-supervised Domain Adaptation for Automatic Quality Control of FLAIR MRIs in a Clinical Data Warehouse -- Towards Foundation Models Learned from Anatomy in Medical Imaging via Self-Supervision -- The Performance of Transferability Metrics does not Translate to Medical Tasks -- DGM-DR: Domain Generalization with Mutual Information Regularized Diabetic Retinopathy Classification -- SEDA: Self-Ensembling ViT with Defensive Distillation and Adversarial Training for robust Chest X-rays Classification -- A Continual Learning Approach for Cross-Domain White Blood Cell Classification -- Metadata Improves Segmentation Through Multitasking Elicitation -- Self-Prompting Large Vision Models for Few-Shot Medical Image Segmentation. |
| Record Nr. | UNISA-996558468103316 |
Koch Lisa
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Domain Adaptation and Representation Transfer [[electronic resource] ] : 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings / / edited by Lisa Koch, M. Jorge Cardoso, Enzo Ferrante, Konstantinos Kamnitsas, Mobarakol Islam, Meirui Jiang, Nicola Rieke, Sotirios A. Tsaftaris, Dong Yang
| Domain Adaptation and Representation Transfer [[electronic resource] ] : 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings / / edited by Lisa Koch, M. Jorge Cardoso, Enzo Ferrante, Konstantinos Kamnitsas, Mobarakol Islam, Meirui Jiang, Nicola Rieke, Sotirios A. Tsaftaris, Dong Yang |
| Autore | Koch Lisa |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (180 pages) |
| Disciplina | 006 |
| Altri autori (Persone) |
CardosoM. Jorge
FerranteEnzo KamnitsasKonstantinos IslamMobarakol JiangMeirui RiekeNicola TsaftarisSotirios A YangDong |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Application software Machine learning Computers Information technology - Management Computer Imaging, Vision, Pattern Recognition and Graphics Computer and Information Systems Applications Machine Learning Computing Milieux Computer Application in Administrative Data Processing |
| ISBN | 3-031-45857-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Domain adaptation of MRI scanners as an alternative to MRI harmonization -- MultiVT: Multiple-Task Framework for Dentistry -- Black-Box Unsupervised Domain Adaptation for Medical Image Segmentation -- PLST: A Pseudo-Labels with a Smooth Transition Strategy for Medical Site Adaptation -- Compositional Representation Learning for Brain Tumor Segmentation -- Hierarchical Compositionality in Hyperbolic Space for Robust Medical Image Segmentation -- Realistic Data Enrichment for Robust Image Segmentation in Kidney Transplant Pathology -- Boosting Knowledge Distillation via Random Fourier Features for Prostate Cancer Grading in Histopathology Images -- Semi-supervised Domain Adaptation for Automatic Quality Control of FLAIR MRIs in a Clinical Data Warehouse -- Towards Foundation Models Learned from Anatomy in Medical Imaging via Self-Supervision -- The Performance of Transferability Metrics does not Translate to Medical Tasks -- DGM-DR: Domain Generalization with Mutual Information Regularized Diabetic Retinopathy Classification -- SEDA: Self-Ensembling ViT with Defensive Distillation and Adversarial Training for robust Chest X-rays Classification -- A Continual Learning Approach for Cross-Domain White Blood Cell Classification -- Metadata Improves Segmentation Through Multitasking Elicitation -- Self-Prompting Large Vision Models for Few-Shot Medical Image Segmentation. |
| Record Nr. | UNINA-9910760287203321 |
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Koch Lisa
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||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Domain adaptation and representation transfer : 4th MICCAI Workshop, DART 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings / / edited by Konstantinos Kamnitsas [and seven others]
| Domain adaptation and representation transfer : 4th MICCAI Workshop, DART 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings / / edited by Konstantinos Kamnitsas [and seven others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (158 pages) |
| Disciplina | 060 |
| Collana | Lecture Notes in Computer Science Ser. |
| Soggetto topico | Artificial intelligence - Medical applications |
| ISBN | 3-031-16852-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996490359503316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Domain Adaptation and Representation Transfer : 4th MICCAI Workshop, DART 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings / / edited by Konstantinos Kamnitsas, Lisa Koch, Mobarakol Islam, Ziyue Xu, Jorge Cardoso, Qi Dou, Nicola Rieke, Sotirios Tsaftaris
| Domain Adaptation and Representation Transfer : 4th MICCAI Workshop, DART 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings / / edited by Konstantinos Kamnitsas, Lisa Koch, Mobarakol Islam, Ziyue Xu, Jorge Cardoso, Qi Dou, Nicola Rieke, Sotirios Tsaftaris |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (158 pages) |
| Disciplina |
060
006.31 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Computer engineering Computer networks Machine learning Computers Application software Computer Vision Computer Engineering and Networks Machine Learning Computing Milieux Computer and Information Systems Applications |
| ISBN | 3-031-16852-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification -- Benchmarking Transformers for Medical Image Classification -- Supervised domain adaptation using gradients transfer for improved medical image analysis -- Stain-AgLr: Stain Agnostic Learning for Computational Histopathology using Domain Consistency and Stain Regeneration Loss -- MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ Segmentation -- Unsupervised site adaptation by intra-site variability alignment -- Discriminative, Restorative, and Adversarial Learning: Stepwise Incremental Pretraining -- POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis -- Feather-Light Fourier Domain Adaptation in Magnetic Resonance Imaging -- Seamless Iterative Semi-Supervised Correction of Imperfect Labels in Microscopy Images -- Task-agnostic Continual Hippocampus Segmentation for Smooth Population Shifts -- Adaptive Optimization with Fewer Epochs Improves Across-Scanner Generalization of U-Net based Medical Image Segmentation -- CateNorm: Categorical Normalization for Robust Medical Image Segmentation. |
| Record Nr. | UNINA-9910595451603321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data [[electronic resource] ] : First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le
| Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data [[electronic resource] ] : First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XVII, 254 p. 113 illus., 79 illus. in color.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Health informatics Image Processing and Computer Vision Artificial Intelligence Health Informatics |
| ISBN | 3-030-33391-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | DART 2019 -- Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation -- Temporal Consistency Objectives Regularize the Learning of Disentangled Representations -- Multi-layer Domain Adaptation for Deep Convolutional Networks -- Intramodality Domain Adaptation using Self Ensembling and Adversarial Training -- Learning Interpretable Disentangled Representations using Adversarial VAEs -- Synthesising Images and Labels Between MR Sequence Types With CycleGAN -- Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning -- Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans -- A Pulmonary Nodule Detection Method Based on Residual Learning and Dense Connection -- Harmonization and Targeted Feature Dropout for Generalized Segmentation: Application to Multi-site Traumatic Brain Injury Images -- Improving Pathological Structure Segmentation Via Transfer Learning Across Diseases -- Generating Virtual Chromoendoscopic Images and Improving Detectability and Classification Performance of Endoscopic Lesions -- MIL3ID 2019 -- Self-supervised learning of inverse problem solvers in medical imaging -- Weakly Supervised Segmentation of Vertebral Bodies with Iterative Slice-propagation -- A Cascade Attention Network for Liver Lesion Classification in Weakly-labeled Multi-phase CT Images -- CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT -- Active Learning Technique for Multimodal Brain Tumor Segmentation using Limited Labeled Images -- Semi-supervised Learning of Fetal Anatomy from Ultrasound -- Multi-modal segmentation with missing MR sequences using pre-trained fusion networks -- More unlabelled data or label more data? A study on semi-supervised laparoscopic image segmentation -- Few-shot Learning with Deep Triplet Networks for Brain Imaging Modality Recognition -- A Convolutional Neural Network Method for Boundary Optimization Enables Few-Shot Learning for Biomedical Image Segmentation -- Transfer Learning from Partial Annotations for Whole Brain Segmentation -- Learning to Segment Skin Lesions from Noisy Annotations -- A Weakly Supervised Method for Instance Segmentation of Biological Cells -- Towards Practical Unsupervised Anomaly Detection on Retinal Images -- Fine tuning U-Net for ultrasound image segmentation: which layers -- Multi-task Learning for Neonatal Brain Segmentation Using 3D Dense-Unet with Dense Attention Guided by Geodesic Distance. |
| Record Nr. | UNISA-996466435303316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data : First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le
| Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data : First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / / edited by Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XVII, 254 p. 113 illus., 79 illus. in color.) |
| Disciplina |
616.07540285
616.0754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Health informatics Image Processing and Computer Vision Artificial Intelligence Health Informatics |
| ISBN | 3-030-33391-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | DART 2019 -- Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation -- Temporal Consistency Objectives Regularize the Learning of Disentangled Representations -- Multi-layer Domain Adaptation for Deep Convolutional Networks -- Intramodality Domain Adaptation using Self Ensembling and Adversarial Training -- Learning Interpretable Disentangled Representations using Adversarial VAEs -- Synthesising Images and Labels Between MR Sequence Types With CycleGAN -- Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning -- Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans -- A Pulmonary Nodule Detection Method Based on Residual Learning and Dense Connection -- Harmonization and Targeted Feature Dropout for Generalized Segmentation: Application to Multi-site Traumatic Brain Injury Images -- Improving Pathological Structure Segmentation Via Transfer Learning Across Diseases -- Generating Virtual Chromoendoscopic Images and Improving Detectability and Classification Performance of Endoscopic Lesions -- MIL3ID 2019 -- Self-supervised learning of inverse problem solvers in medical imaging -- Weakly Supervised Segmentation of Vertebral Bodies with Iterative Slice-propagation -- A Cascade Attention Network for Liver Lesion Classification in Weakly-labeled Multi-phase CT Images -- CT Data Curation for Liver Patients: Phase Recognition in Dynamic Contrast-Enhanced CT -- Active Learning Technique for Multimodal Brain Tumor Segmentation using Limited Labeled Images -- Semi-supervised Learning of Fetal Anatomy from Ultrasound -- Multi-modal segmentation with missing MR sequences using pre-trained fusion networks -- More unlabelled data or label more data? A study on semi-supervised laparoscopic image segmentation -- Few-shot Learning with Deep Triplet Networks for Brain Imaging Modality Recognition -- A Convolutional Neural Network Method for Boundary Optimization Enables Few-Shot Learning for Biomedical Image Segmentation -- Transfer Learning from Partial Annotations for Whole Brain Segmentation -- Learning to Segment Skin Lesions from Noisy Annotations -- A Weakly Supervised Method for Instance Segmentation of Biological Cells -- Towards Practical Unsupervised Anomaly Detection on Retinal Images -- Fine tuning U-Net for ultrasound image segmentation: which layers -- Multi-task Learning for Neonatal Brain Segmentation Using 3D Dense-Unet with Dense Attention Guided by Geodesic Distance. |
| Record Nr. | UNINA-9910349274803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||