11 citations · 18 across the 8 of their papers we have counts for
8 papers
Improving the performance of object detection by preserving label distribution
Heewon Lee, Sangtae Ahn
Object detection is a task that performs position identification and label classification of objects in images or videos. The information obtained through this process plays an ess…
Deep learning-based reconstruction of highly accelerated 3D MRI
Sangtae Ahn, Uri Wollner, Graeme McKinnon +10
Purpose: To accelerate brain 3D MRI scans by using a deep learning method for reconstructing images from highly-undersampled multi-coil k-space data Methods: DL-Speed, an unrolled…
A Fast Convergent Ordered-Subsets Algorithm with Subiteration-Dependent Preconditioners for PET Image Reconstruction
Jianfeng Guo, C. Ross Schmidtlein, Andrzej Krol +5
We investigated the imaging performance of a fast convergent ordered-subsets algorithm with subiteration-dependent preconditioners (SDPs) for positron emission tomography (PET) ima…
Artificial Intelligence in PET: an Industry Perspective
Arkadiusz Sitek, Sangtae Ahn, Evren Asma +6
Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI has t…
Adaptive Gradient Balancing for Undersampled MRI Reconstruction and Image-to-Image Translation
Itzik Malkiel, Sangtae Ahn, Valentina Taviani +3
Recent accelerated MRI reconstruction models have used Deep Neural Networks (DNNs) to reconstruct relatively high-quality images from highly undersampled k-space data, enabling muc…
A Novel Approach for Correcting Multiple Discrete Rigid In-Plane Motions Artefacts in MRI Scans
Michael Rotman, Rafi Brada, Israel Beniaminy +3
Motion artefacts created by patient motion during an MRI scan occur frequently in practice, often rendering the scans clinically unusable and requiring a re-scan. While many method…