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Record Nr. |
UNISA996635671303316 |
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Autore |
Bathula Deepti R |
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Titolo |
Machine 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 Xiao |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
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ISBN |
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9783031787614 |
9783031787607 |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (187 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 15266 |
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Altri autori (Persone) |
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Benet NirmalaAnoop |
DvornekNicha C |
GovindarajanSindhuja T |
HabesMohamad |
KumarVinod |
NebliAhmed |
WolfersThomas |
XiaoYiming |
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Disciplina |
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Soggetti |
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Computer vision |
Machine learning |
Computers |
Social sciences - Data processing |
Computer Vision |
Machine Learning |
Computing Milieux |
Computer Application in Social and Behavioral Sciences |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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-- Machine learning. -- Parkinson's Disease Detection from Resting State EEG using Multi-Head Graph Structure Learning with Gradient |
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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. |
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Sommario/riassunto |
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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. |
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