A contrast augmentation approach to improve multi-scanner generalization in MRI
Most data-driven methods are very susceptible to data variability. This problem is particularly
apparent when applying Deep Learning (DL) to brain Magnetic Resonance Imaging (MRI) …
apparent when applying Deep Learning (DL) to brain Magnetic Resonance Imaging (MRI) …
ESPA: An Unsupervised Harmonization Framework via Enhanced Structure Preserving Augmentation
M Eshaghzadeh Torbati, DS Minhas, AP Tafti… - … Conference on Medical …, 2024 - Springer
The rising interest in pooling neuroimaging data from various sources presents challenges
regarding scanner variability, known as scanner effects. While numerous harmonization …
regarding scanner variability, known as scanner effects. While numerous harmonization …
[HTML][HTML] MISPEL: A supervised deep learning harmonization method for multi-scanner neuroimaging data
ME Torbati, DS Minhas, CM Laymon, P Maillard… - Medical image …, 2023 - Elsevier
Large-scale data obtained from aggregation of already collected multi-site neuroimaging
datasets has brought benefits such as higher statistical power, reliability, and robustness to …
datasets has brought benefits such as higher statistical power, reliability, and robustness to …
MISPEL: A deep learning approach for harmonizing multi-scanner matched neuroimaging data
ME Torbati, DS Minhas, CM Laymon, P Maillard… - bioRxiv, 2022 - biorxiv.org
Large-scale data obtained from aggregation of already collected multi-site neuroimaging
datasets has been brought benefits such as higher statistical power, reliability, and …
datasets has been brought benefits such as higher statistical power, reliability, and …
Harmonization of Multi-Scanner Magnetic Resonance Imaging Data
ME Torbati - 2024 - search.proquest.com
The integration of datasets from multiple sites or scanners in neuroimaging studies has
become increasingly prevalent. However, the presence of substantial technical variability …
become increasingly prevalent. However, the presence of substantial technical variability …
[PDF][PDF] ESPA: An Unsupervised Harmonization Framework via Enhanced Structure Preserving Augmentation
METDS Minhas, AP Tafti, CS DeCarli, DL Tudorascu… - papers.miccai.org
The rising interest in pooling neuroimaging data from various sources presents challenges
regarding scanner variability, known as scanner effects. While numerous harmonization …
regarding scanner variability, known as scanner effects. While numerous harmonization …