Aberrant white matter networks in methamphetamine-dependent patients and its application in support vector machine-based classification

AI & Brain Tumours

    AI in Stroke & Hemorrhage Detection

      An Analysis of the Interpretability of Neural Networks trained on Magnetic Resonance Imaging for Stroke Outcome Prediction

      Brain atrophy and machine learning algorithms on the prediction of dementia development

      CE-Net: multi-inputs contrast enhancement network for nasopharyngeal carcinoma contrast enhanced T1-weighted MR synthesis

      Classification of Alzheimer's Disease Based on Amyloid-PET using Random Forest Ensemble

      Clinical Application of Twelve-fold Accelerated Submillimeter Whole Brain 3D-T2 weighted Imaging with Deep Learning Reconstruction

      A Comparative and Summative Study of Radiomics-Based Overall Survival Prediction in Glioblastoma Patients

      A comparison of three whole brain segmentation methods for in vivo manganese enhanced MRI in animal models of Alzheimer's disease

      A deep learning approach to estimate voxelwise cardiac-related brain pulsatility from BOLD MRI

      Deep Learning Identifies Neuroimaging Signatures of Alzheimer's Disease Using Structural and Artificial Functional MRI Data

      Deep learning prediction of retrieved stroke thrombus RBC content using quantitative, multiparametric MRI

      Deep Learning-based Automatic Detection and Segmentation of Brain Metastases Using Multi-Task Learning with 3D Black-Blood and GRE Imaging

      Deep learning-based Cerebral Microbleeds detection on quantitative susceptibility mapping(QSM) for Stroke Cohort

      DL-BET - A deep learning based tool for automatic brain extraction from structural magnetic resonance images in mice.

      Image-to-image translation of 3T to 7T MRI using Generative Adversarial Networks: A step towards longitudinal harmonization

      Improved Automated Hippocampus Segmentation using Deep Neural Networks

      Improved Segmentation of MR Brain Images by Integrating Bayesian and Deep Learning-Based Classification

      Improving the generalizability of convolutional neural networks for T2-lesion segmentation of gliomas in the post-treatment setting

      Increasing Feature Sparsity in Alzheimer's Disease Classification with Relevance-Guided Deep Learning

      Learning from Deep Learning

        Machine Learning Evaluation of the Effects of Prematurity on Regional BOLD Resting-State Activity and Connectivity, and T1-w Brain Volumes.

        Machine Learning-based Analysis of Heterogeneous, Multi-center MR Datasets: Impact of Scan Variability

        Mapping transient coactivity patterns of brain in latent space with variational autoencoder neural network

        Author:Kaiming Li  Xiaoping Hu  

        Session Type:Digital Poster  

        Session Date:Wednesday, 19 May 2021  

        Topic:Emerging Applications of AI in Neuroimaging  

        Session Name:Emerging Applications of AI in Neuroimaging for CES I  

        Program Number:3497  

        Room Session:Concurrent 6  

        Institution:UC Riverside  

        Novel machine learning method for clinically significant cortical lesion detection in multiple sclerosis

        Performance evaluation of machine learning algorithms for multiple sclerosis phenotype classification using 7-Tesla MRI and clinical features

        Preoperative MR Radiomics and ADC Value for Prediction of Progression and Recurrence in Meningiomas

        Preoperative MR Radiomics for Prediction of Progression and Recurrence in Non-functional Pituitary Macroadenomas

        Radio-pathomic models trained with autopsy tissue samples aligned to MP-MRI predict histopathological features in brain cancer patients.

        Rapid Estimation of Multiple Diffusion Maps from Undersampled Q-Space Data: A Comparison of Three Deep Learning Approaches

        Role of AI in Image Acquisition & Processing

          Self-Supervised Transfer Learning for Infant Cerebellum Segmentation with Multi-Domain MRIs

          A semi-supervised level-set loss for white matter hyperintensities segmentation on FLAIR without manual labels

          Simulation of brain deficits on MRI: A novel approach of 'ground truth' generation for machine learning

          Task-aware 3D-Convolutional Neural Networks for Detailed Brain Parcellation

          White matter hyperintensity volumes and cognition: Assessment of a deep learning-based lesion detection and quantification algorithm on ADNI