Katalog der Deutschen Nationalbibliothek

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

Cham: Springer Nature Switzerland, Imprint: Springer
2025

1st ed. 2025

Online-Ressource, XIX, 262 p. 99 illus., 95 illus. in color. : online resource.

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

978-3-031-84525-3

Englisch

Deutschland

Medizin, Gesundheit

Computer Imaging, Vision, Pattern Recognition and Graphics.

616.075

Lecture Notes in Computer Science ; 15401

urn:nbn:de:101:1-2504130410094.161656861840 (URN)
10.1007/978-3-031-84525-3 (DOI)

136294548X