Haris I. Sair
According to our database1,
Haris I. Sair
authored at least 23 papers
between 2013 and 2024.
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Bibliography
2024
Emergent Language Symbolic Autoencoder (ELSA) with Weak Supervision to Model Hierarchical Brain Networks.
CoRR, 2024
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
2023
J. Imaging Inform. Medicine, 2023
Active Learning in Brain Tumor Segmentation with Uncertainty Sampling, Annotation Redundancy Restriction, and Data Initialization.
CoRR, 2023
2022
RefineNet: An Automated Framework to Generate Task and Subject-Specific Brain Parcellations for Resting-State fMRI Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Proceedings of the Advances in Visual Computing - 17th International Symposium, 2022
2021
Automated eloquent cortex localization in brain tumor patients using multi-task graph neural networks.
Medical Image Anal., 2021
A Multi-scale Spatial and Temporal Attention Network on Dynamic Connectivity to Localize the Eloquent Cortex in Brain Tumor Patients.
Proceedings of the Information Processing in Medical Imaging, 2021
2020
A Multi-task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity.
Proceedings of the Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology, 2020
2019
Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks.
J. Digit. Imaging, 2019
Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs.
J. Digit. Imaging, 2019
Functional Magnetic Resonance Imaging Activation Optimization in the Setting of Brain Tumor-Induced Neurovascular Uncoupling Using Resting-State Blood Oxygen Level-Dependent Amplitude of Low Frequency Fluctuations.
Brain Connect., 2019
A Novel Graph Neural Network to Localize Eloquent Cortex in Brain Tumor Patients from Resting-State fMRI Connectivity.
Proceedings of the Connectomics in NeuroImaging - Third International Workshop, 2019
2018
Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields.
Proceedings of the Connectomics in NeuroImaging - Second International Workshop, 2018
2017
Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.
Brain Connect., 2017
The Resting-State Functional Magnetic Resonance Imaging Regional Homogeneity Metrics - Kendall's Coefficient of Concordance-Regional Homogeneity and Coherence-Regional Homogeneity - Are Valid Indicators of Tumor-Related Neurovascular Uncoupling.
Brain Connect., 2017
2016
Reporting of Resting-State Functional Magnetic Resonance Imaging Preprocessing Methodologies.
Brain Connect., 2016
Demonstration of Brain Tumor-Induced Neurovascular Uncoupling in Resting-State fMRI at Ultrahigh Field.
Brain Connect., 2016
A machine learning based approach for identifying traumatic brain injury patients for whom a head CT scan can be avoided.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016
2015
Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.
Comput. Stat. Data Anal., 2015
2013
Mapping the effects of ApoE4, age and cognitive status on 18F-florbetapir PET measured regional cortical patterns of beta-amyloid density and growth.
NeuroImage, 2013