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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
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops : LDTM 2024, MMMI/ML4MHD 2024, ML-CDS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6–10, 2024, Proceedings / / edited by Anna Schroder, Xiang Li, Tanveer Syeda-Mahmood, Neil P. Oxtoby, Alexandra Young, Alessa Hering, Tejas S. Mathai, Pritam Mukherjee, Sven Kuckertz, Tiantian He, Isaac Llorente-Saguer, Andreas Maier, Satyananda Kashyap, Hayit Greenspan, Anant Madabhushi
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops : LDTM 2024, MMMI/ML4MHD 2024, ML-CDS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6–10, 2024, Proceedings / / edited by Anna Schroder, Xiang Li, Tanveer Syeda-Mahmood, Neil P. Oxtoby, Alexandra Young, Alessa Hering, Tejas S. Mathai, Pritam Mukherjee, Sven Kuckertz, Tiantian He, Isaac Llorente-Saguer, Andreas Maier, Satyananda Kashyap, Hayit Greenspan, Anant Madabhushi |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XIX, 262 p. 99 illus., 95 illus. in color.) |
| Disciplina | 006 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Computer Imaging, Vision, Pattern Recognition and Graphics |
| ISBN | 3-031-84525-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | LDTM Workshop -- Disease Progression Modelling and Stratification for detecting sub-trajectories in the natural history of pathologies: application toParkinson’s Disease trajectory modelling -- Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series -- Individualized multi-horizon MRI trajectory prediction for Alzheimer’s Disease -- Toward, for the Alzheimer’s Disease Neuroimaging Initiative Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling -- BachCuadraSegHeD: Segmentation of Heterogeneous Data for Multiple SclerosisLesions with Anatomical Constraints -- Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting -- Registration of Longitudinal Liver Examinations for Tumor ProgressAssessment -- Tracking lesion evolution using a Boundary Enhanced Approach for MS change segmentation (BEAMS) -- A Radiological-based Coordinate System for the Human Body: A Proof-of-Concept -- MMMI-ML4MHD Workshop -- Language Models Meet Anomaly Detection for Better Interpretabilityand Generalizability -- A Diffusion Model Embedded WCSAU-Net for 3D MRI Brain Tumor Segmentation -- Predicting Human Brain States with Transformer -- Modality Image Quality Prediction for Time-Resolved CT fromBreathing Signals -- RATNUS: Rapid, Automatic Thalamic Nuclei Segmentation using Multimodal MRI inputs -- HyperMM : Robust Multimodal Learning with Varying-sized Inputs -- EMIT: H&E to Multiplex-immunohistochemistry Image Translation with Dual-Branch Pix2pix Generator -- Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis -- ML-CDS Workshop -- MedPromptX: Grounded Multimodal Prompting for Chest X-rayDiagnosis -- Predicting Stroke through Retinal Graphs and Multimodal Self-supervised Learning -- Multimodality for Diagnosis of Asian Choroidal Vasculopathy: Resultsfrom a Novel Dataset and Deep-learning Experiments -- Multimodality Frequency Feature Customized Learning for PediatricVentricular Septal Defects Identification. |
| Record Nr. | UNINA-9910996484603321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops : LDTM 2024, MMMI/ML4MHD 2024, ML-CDS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6–10, 2024, Proceedings / / edited by Anna Schroder, Xiang Li, Tanveer Syeda-Mahmood, Neil P. Oxtoby, Alexandra Young, Alessa Hering, Tejas S. Mathai, Pritam Mukherjee, Sven Kuckertz, Tiantian He, Isaac Llorente-Saguer, Andreas Maier, Satyananda Kashyap, Hayit Greenspan, Anant Madabhushi
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops : LDTM 2024, MMMI/ML4MHD 2024, ML-CDS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6–10, 2024, Proceedings / / edited by Anna Schroder, Xiang Li, Tanveer Syeda-Mahmood, Neil P. Oxtoby, Alexandra Young, Alessa Hering, Tejas S. Mathai, Pritam Mukherjee, Sven Kuckertz, Tiantian He, Isaac Llorente-Saguer, Andreas Maier, Satyananda Kashyap, Hayit Greenspan, Anant Madabhushi |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XIX, 262 p. 99 illus., 95 illus. in color.) |
| Disciplina | 006 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Computer Imaging, Vision, Pattern Recognition and Graphics |
| ISBN | 3-031-84525-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | LDTM Workshop -- Disease Progression Modelling and Stratification for detecting sub-trajectories in the natural history of pathologies: application toParkinson’s Disease trajectory modelling -- Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series -- Individualized multi-horizon MRI trajectory prediction for Alzheimer’s Disease -- Toward, for the Alzheimer’s Disease Neuroimaging Initiative Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling -- BachCuadraSegHeD: Segmentation of Heterogeneous Data for Multiple SclerosisLesions with Anatomical Constraints -- Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting -- Registration of Longitudinal Liver Examinations for Tumor ProgressAssessment -- Tracking lesion evolution using a Boundary Enhanced Approach for MS change segmentation (BEAMS) -- A Radiological-based Coordinate System for the Human Body: A Proof-of-Concept -- MMMI-ML4MHD Workshop -- Language Models Meet Anomaly Detection for Better Interpretabilityand Generalizability -- A Diffusion Model Embedded WCSAU-Net for 3D MRI Brain Tumor Segmentation -- Predicting Human Brain States with Transformer -- Modality Image Quality Prediction for Time-Resolved CT fromBreathing Signals -- RATNUS: Rapid, Automatic Thalamic Nuclei Segmentation using Multimodal MRI inputs -- HyperMM : Robust Multimodal Learning with Varying-sized Inputs -- EMIT: H&E to Multiplex-immunohistochemistry Image Translation with Dual-Branch Pix2pix Generator -- Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis -- ML-CDS Workshop -- MedPromptX: Grounded Multimodal Prompting for Chest X-rayDiagnosis -- Predicting Stroke through Retinal Graphs and Multimodal Self-supervised Learning -- Multimodality for Diagnosis of Asian Choroidal Vasculopathy: Resultsfrom a Novel Dataset and Deep-learning Experiments -- Multimodality Frequency Feature Customized Learning for PediatricVentricular Septal Defects Identification. |
| Record Nr. | UNISA-996655268903316 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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