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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part II / / edited by Spyridon Bakas, Alessandro Crimi, Ujjwal Baid, Sylwia Malec, Monika Pytlarz, Bhakti Baheti, Maximilian Zenk, Reuben Dorent
| Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part II / / edited by Spyridon Bakas, Alessandro Crimi, Ujjwal Baid, Sylwia Malec, Monika Pytlarz, Bhakti Baheti, Maximilian Zenk, Reuben Dorent |
| Autore | Bakas Spyridon |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (256 pages) |
| Disciplina | 616.8 |
| Altri autori (Persone) |
CrimiAlessandro
BaidUjjwal MalecSylwia PytlarzMonika BahetiBhakti ZenkMaximilian DorentReuben |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Medical informatics Social sciences - Data processing Application software Education - Data processing Artificial intelligence Computer Vision Health Informatics Computer Application in Social and Behavioral Sciences Computer and Information Systems Applications Computers and Education Artificial Intelligence |
| ISBN | 3-031-44153-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Applying Quadratic Penalty Method for Intensity-based Deformable Image Registration on BraTS-Reg Challenge 2022 -- WSSAMNet: Weakly Supervised Semantic Attentive Medical Image Registration Network -- Self-supervised iRegNet for the Registration of Longitudinal Brain MRI of Diffuse Glioma Patients -- 3D Inception-Based TransMorph: Pre- and Post-operative Multi-contrast MRI Registration in Brain Tumors -- Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation and Koos Grade Prediction based on Semi-Supervised Contrastive Learning -- Koos Classification of Vestibular Schwannoma via Image Translation-Based Unsupervised Cross-Modality Domain Adaptation -- MS-MT: Multi-Scale Mean Teacher with Contrastive Unpaired Translation for Cross-Modality Vestibular Schwannoma and Cochlea Segmentation -- An Unpaired Cross-modality Segmentation Framework Using Data Augmentation and Hybrid Convolutional Networks for Segmenting Vestibular Schwannoma and Cochlea.-Weakly Unsupervised Domain Adaptation for Vestibular Schwannoma Segmentation -- Multi-view Cross-Modality MR Image Translation for Vestibular Schwannoma and Cochlea Segmentation -- Enhancing Data Diversity for Self-training Based Unsupervised Cross-modality Vestibular Schwannoma and Cochlea Segmentation -- Regularized Weight Aggregation in Networked Federated Learning for Glioblastoma Segmentation -- A Local Score Strategy for Weight Aggregation in Federated Learning -- Ensemble Outperforms Single Models in Brain Tumor Segmentation -- FeTS Challenge 2022 Task 1: Implementing FedMGDA+ and a new partitioning -- Efficient Federated Tumor Segmentation via Parameter Distance Weighted Aggregation and Client Pruning -- Hybrid Window Attention Based Transformer Architecture for Brain Tumor Segmentation -- Robust Learning Protocol for Federated Tumor Segmentation Challenge -- Model Aggregation for Federated Learning Considering Non-IID and Imbalanced Data Distribution -- FedPIDAvg: A PID controller inspired aggregation method for Federated Learning -- Federated Evaluation of nnU-Nets Enhanced with Domain Knowledge for Brain Tumor Segmentation -- Experimenting FedML and NVFLARE for Federated Tumor Segmentation Challenge. |
| Record Nr. | UNINA-9910831012003321 |
Bakas Spyridon
|
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part II / / edited by Spyridon Bakas, Alessandro Crimi, Ujjwal Baid, Sylwia Malec, Monika Pytlarz, Bhakti Baheti, Maximilian Zenk, Reuben Dorent
| Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part II / / edited by Spyridon Bakas, Alessandro Crimi, Ujjwal Baid, Sylwia Malec, Monika Pytlarz, Bhakti Baheti, Maximilian Zenk, Reuben Dorent |
| Autore | Bakas Spyridon |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (256 pages) |
| Disciplina | 616.8 |
| Altri autori (Persone) |
CrimiAlessandro
BaidUjjwal MalecSylwia PytlarzMonika BahetiBhakti ZenkMaximilian DorentReuben |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Medical informatics Social sciences - Data processing Application software Education - Data processing Artificial intelligence Computer Vision Health Informatics Computer Application in Social and Behavioral Sciences Computer and Information Systems Applications Computers and Education Artificial Intelligence |
| ISBN | 3-031-44153-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Applying Quadratic Penalty Method for Intensity-based Deformable Image Registration on BraTS-Reg Challenge 2022 -- WSSAMNet: Weakly Supervised Semantic Attentive Medical Image Registration Network -- Self-supervised iRegNet for the Registration of Longitudinal Brain MRI of Diffuse Glioma Patients -- 3D Inception-Based TransMorph: Pre- and Post-operative Multi-contrast MRI Registration in Brain Tumors -- Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation and Koos Grade Prediction based on Semi-Supervised Contrastive Learning -- Koos Classification of Vestibular Schwannoma via Image Translation-Based Unsupervised Cross-Modality Domain Adaptation -- MS-MT: Multi-Scale Mean Teacher with Contrastive Unpaired Translation for Cross-Modality Vestibular Schwannoma and Cochlea Segmentation -- An Unpaired Cross-modality Segmentation Framework Using Data Augmentation and Hybrid Convolutional Networks for Segmenting Vestibular Schwannoma and Cochlea.-Weakly Unsupervised Domain Adaptation for Vestibular Schwannoma Segmentation -- Multi-view Cross-Modality MR Image Translation for Vestibular Schwannoma and Cochlea Segmentation -- Enhancing Data Diversity for Self-training Based Unsupervised Cross-modality Vestibular Schwannoma and Cochlea Segmentation -- Regularized Weight Aggregation in Networked Federated Learning for Glioblastoma Segmentation -- A Local Score Strategy for Weight Aggregation in Federated Learning -- Ensemble Outperforms Single Models in Brain Tumor Segmentation -- FeTS Challenge 2022 Task 1: Implementing FedMGDA+ and a new partitioning -- Efficient Federated Tumor Segmentation via Parameter Distance Weighted Aggregation and Client Pruning -- Hybrid Window Attention Based Transformer Architecture for Brain Tumor Segmentation -- Robust Learning Protocol for Federated Tumor Segmentation Challenge -- Model Aggregation for Federated Learning Considering Non-IID and Imbalanced Data Distribution -- FedPIDAvg: A PID controller inspired aggregation method for Federated Learning -- Federated Evaluation of nnU-Nets Enhanced with Domain Knowledge for Brain Tumor Segmentation -- Experimenting FedML and NVFLARE for Federated Tumor Segmentation Challenge. |
| Record Nr. | UNISA-996585471703316 |
|
Bakas Spyridon
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||