04727nam 22007215 450 99663567130331620250626164330.09783031787614(electronic bk.)978303178760710.1007/978-3-031-78761-4(MiAaPQ)EBC31822019(Au-PeEL)EBL31822019(CKB)36947406000041(DE-He213)978-3-031-78761-4(OCoLC)1478697090(EXLCZ)993694740600004120241207d2025 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine Learning in Clinical Neuroimaging 7th International Workshop, MLCN 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings /edited by Deepti R. Bathula, Anoop Benet Nirmala, Nicha C. Dvornek, Sindhuja T. Govindarajan, Mohamad Habes, Vinod Kumar, Ahmed Nebli, Thomas Wolfers, Yiming Xiao1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (187 pages)Lecture Notes in Computer Science,1611-3349 ;15266Print version: Bathula, Deepti R. Machine Learning in Clinical Neuroimaging Cham : Springer,c2025 9783031787607 -- Machine learning. -- Parkinson's Disease Detection from Resting State EEG using Multi-Head Graph Structure Learning with Gradient Weighted Graph Attention Explanations. -- ProxiMO: Proximal Multi-Operator Networks for Quantitative Susceptibility Mapping. -- Brain-Cognition Fingerprinting via Graph-GCCA with Contrastive Learning. -- HyperBrain: Anomaly Detection for Temporal Hypergraph Brain Networks. -- SpaRG - Sparsely Reconstructed Graphs for Generalizable fMRI Analysis. -- A Lightweight 3D Conditional Diffusion Model for Self-Explainable Brain Age Prediction in Adults and Children. -- SOE: SO(3)-Equivariant 3D MRI Encoding. -- Towards a foundation model for cortical folding. -- Clinical Applications. -- A Lesion-aware Edge-based Graph Neural Network for Predicting Language Ability in Patients with Post-stroke Aphasia. -- DISARM: Disentangled Scanner-free Image Generation via Unsupervised Image2Image Translation. -- Segmenting Small Stroke Lesions with Novel Labeling Strategies. -- A Progressive Single-Modality to Multi-Modality Classification Framework for Alzheimer’s Disease Sub-type Diagnosis. -- Surface-based parcellation and vertex-wise analysis of ultra high-resolution ex vivo 7 tesla MRI in Alzheimer's disease and related dementias. -- Self-Supervised Pre-training Tasks for an fMRI Time-series Transformer in Autism Detection. -- Is Your Style Transfer Doing Anything Useful? An Investigation Into Hippocampus Segmentation and the Role of Preprocessing. -- GAMing the Brain: Investigating the Cross-modal Relationships between Functional Connectivity and Structural Features using Generalized Additive Models.This book constitutes the refereed proceedings of the 7th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2024, held in Conjunction with MICCAI 2024 in Marrakesh, Morocco, on 10th October 2024. The 16 full papers presented in this volume were carefully reviewed and selected from 28 submissions. They are grouped into the following topics: machine learning; clinical applications.Lecture Notes in Computer Science,1611-3349 ;15266Computer visionMachine learningComputersSocial sciencesData processingComputer VisionMachine LearningComputing MilieuxComputer Application in Social and Behavioral SciencesComputer vision.Machine learning.Computers.Social sciencesData processing.Computer Vision.Machine Learning.Computing Milieux.Computer Application in Social and Behavioral Sciences.006.37Bathula Deepti R1431708Benet Nirmala Anoop1782611Dvornek Nicha C1431709Govindarajan Sindhuja T1431710Habes Mohamad1431711Kumar Vinod767644Nebli Ahmed1782612Wolfers Thomas1431713Xiao Yiming1431714MiAaPQMiAaPQMiAaPQ996635671303316Machine Learning in Clinical Neuroimaging4309020UNISA