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Publication search results
found 17 matches
- 2025
- Deepti R. Bathula
, Anoop Benet Nirmala, Nicha C. Dvornek, Sindhuja Tirumalai Govindarajan, Mohamad Habes, Vinod Kumar, Ahmed Nebli, Thomas Wolfers, Yiming Xiao:
Machine Learning in Clinical Neuroimaging - 7th International Workshop, MLCN 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. Lecture Notes in Computer Science 15266, Springer 2025, ISBN 978-3-031-78760-7 [contents] - 2024
- Luca Caldera, Lara Cavinato, Andrea Cappozzo, Isabella Cama, Sara Garbarino, Alessio Cirone, Raffaele Lodi, Fabrizio Tagliavini, Anna Nigri, Silvia De Francesco, Francesca Ieva, RIN-Neuroimaging Network:
DISARM: Disentangled Scanner-Free Image Generation via Unsupervised Image2Image Translation. MLCN@MICCAI 2024: 102-112 - Zijian Chen, Maria Varkanitsa, Prakash Ishwar, Janusz Konrad, Margrit Betke, Swathi Kiran, Archana Venkataraman:
A Lesion-Aware Edge-Based Graph Neural Network for Predicting Language Ability in Patients with Post-stroke Aphasia. MLCN@MICCAI 2024: 91-101 - Camila González, Yanis Miraoui, Yiran Fan, Ehsan Adeli-Mosabbeb, Kilian M. Pohl:
SpaRG: Sparsely Reconstructed Graphs for Generalizable fMRI Analysis. MLCN@MICCAI 2024: 46-56 - Shizhe He, Magdalini Paschali, Jiahong Ouyang, Adnan Masood, Akshay Chaudhari, Ehsan Adeli-Mosabbeb:
SOE: SO(3)-Equivariant 3D MRI Encoding. MLCN@MICCAI 2024: 68-77 - Hoda Kalabizadeh, Ludovica Griffanti, Pak-Hei Yeung, Natalie Voets, Grace Gillis, Clare Mackay, Ana IL Namburete, Nicola K. Dinsdale, Konstantinos Kamnitsas:
Is Your Style Transfer Doing Anything Useful? An Investigation into Hippocampus Segmentation and the Role of Preprocessing. MLCN@MICCAI 2024: 155-165 - Arunkumar Kannan, Brian Caffo, Archana Venkataraman:
GAMing the Brain: Investigating the Cross-Modal Relationships Between Functional Connectivity and Structural Features Using Generalized Additive Models. MLCN@MICCAI 2024: 166-175 - Pulkit Khandelwal, Michael Tran Duong, Lisa Levorse, Constanza Fuentes, Amanda Denning, Winifred Trotman, Ranjit Ittyerah, Alejandra Bahena, Theresa Schuck, Marianna Gabrielyan, Karthik Prabhakaran, Daniel T. Ohm, Gabor Mizsei, John Robinson, Mónica Muñoz López, John A. Detre, Edward B. Lee, David J. Irwin, Corey McMillan, M. Dylan Tisdall, Sandhitsu R. Das, David A. Wolk, Paul A. Yushkevich:
Surface-Based Parcellation and Vertex-wise Analysis of Ultra High-resolution ex vivo 7 tesla MRI in Alzheimer's disease and related dementias. MLCN@MICCAI 2024: 134-144 - Julien Laval, Joël Chavas, Vanessa Troiani, William Snyder, Marisa Patti, Mylène Moyal, Marion Plaze, Arnaud Cachia, Zhongyi Sun, Vincent Frouin, Pietro Gori, Denis Rivière, Jean-François Mangin:
Towards a Foundation Model for Cortical Folding. MLCN@MICCAI 2024: 78-88 - Yuxiao Liu, Mianxin Liu, Yuanwang Zhang, Kaicong Sun, Dinggang Shen:
A Progressive Single-Modality to Multi-modality Classification Framework for Alzheimer's Disease Sub-type Diagnosis. MLCN@MICCAI 2024: 123-133 - Christopher Neves, Yong Zeng, Yiming Xiao:
Parkinson's Disease Detection from Resting State EEG Using Multi-head Graph Structure Learning with Gradient Weighted Graph Attention Explanations. MLCN@MICCAI 2024: 3-12 - Shmuel Orenstein, Zhenghan Fang, Hyeong-Geol Shin, Peter C. M. van Zijl, Xu Li, Jeremias Sulam:
ProxiMO: Proximal Multi-operator Networks for Quantitative Susceptibility Mapping. MLCN@MICCAI 2024: 13-23 - Sadaf Sadeghian, Xiaoxiao Li, Margo I. Seltzer:
HyperBrain: Anomaly Detection for Temporal Hypergraph Brain Networks. MLCN@MICCAI 2024: 35-45 - Liang Shang, Zhengyang Lou, Andrew L. Alexander, Vivek Prabhakaran, William A. Sethares, Veena A. Nair, Nagesh Adluru:
Segmenting Small Stroke Lesions with Novel Labeling Strategies. MLCN@MICCAI 2024: 113-122 - Yixin Wang, Wei Peng, Yu Zhang, Ehsan Adeli-Mosabbeb, Qingyu Zhao, Kilian M. Pohl:
Brain-Cognition Fingerprinting via Graph-GCCA with Contrastive Learning. MLCN@MICCAI 2024: 24-34 - Matthias Wilms, Ahmad O. Ahsan, Erik Y. Ohara, Gabrielle Dagasso, Elizabeth Macavoy, Emma A. M. Stanley, Vibujithan Vigneshwaran, Nils D. Forkert:
A Lightweight 3D Conditional Diffusion Model for Self-explainable Brain Age Prediction in Adults and Children. MLCN@MICCAI 2024: 57-67 - Yinchi Zhou, Peiyu Duan, Yuexi Du, Nicha C. Dvornek:
Self-supervised Pre-training Tasks for an fMRI Time-Series Transformer in Autism Detection. MLCN@MICCAI 2024: 145-154
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