257 citations · 635 across the 15 of their papers we have counts for
7 papers · 1 filter
Brain MRI-to-PET Synthesis using 3D Convolutional Attention Networks
Ramy Hussein, David Shin, Moss Zhao +4
Accurate quantification of cerebral blood flow (CBF) is essential for the diagnosis and assessment of a wide range of neurological diseases. Positron emission tomography (PET) with…
Self-Supervised Longitudinal Neighbourhood Embedding
Jiahong Ouyang, Qingyu Zhao, Ehsan Adeli +4
Longitudinal MRIs are often used to capture the gradual deterioration of brain structure and function caused by aging or neurological diseases. Analyzing this data via machine lear…
Representation Disentanglement for Multi-modal brain MR Analysis
Jiahong Ouyang, Ehsan Adeli, Kilian M. Pohl +2
Multi-modal MRIs are widely used in neuroimaging applications since different MR sequences provide complementary information about brain structures. Recent works have suggested tha…
Random Bundle: Brain Metastases Segmentation Ensembling through Annotation Randomization
Darvin Yi, Endre Grøvik, Michael Iv +3
We introduce a novel ensembling method, Random Bundle (RB), that improves performance for brain metastases segmentation. We create our ensemble by training each network on our data…
Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives
Darvin Yi, Endre Grøvik, Michael Iv +3
Deep learning has proven to be an essential tool for medical image analysis. However, the need for accurately labeled input data, often requiring time- and labor-intensive annotati…
200x Low-dose PET Reconstruction using Deep Learning
Junshen Xu, Enhao Gong, John Pauly +1
Positron emission tomography (PET) is widely used in various clinical applications, including cancer diagnosis, heart disease and neuro disorders. The use of radioactive tracer in…
Deep Generative Adversarial Networks for Compressed Sensing Automates MRI
Morteza Mardani, Enhao Gong, Joseph Y. Cheng +8
Magnetic resonance image (MRI) reconstruction is a severely ill-posed linear inverse task demanding time and resource intensive computations that can substantially trade off {\it a…