- Brain Biomechanics Imaging Resources now has 30 datasets available for download.
- 10 subjects from the Henry Jackson Foundation, imaged with tagged magnetic resonance.
- 10 subjects from University of Delaware, imaged with high resolution magnetic resonance elastography at multiple frequencies (30Hz, 50Hz, 70Hz).
- 10 subjects from Washington University in St. Louis, imaged with magnetic resonance elastography at multiple frequencies (20Hz, 30Hz, 50Hz, 70Hz, 90Hz).
- All data includes structural magnetic resonance images (T1-w, T2-w) and diffusion weighted images.
- The structural images have been processed with SLANT-MACRUISE. The diffusion images with TORTOISE.
- Individual subjects can be downloaded or complete site sets.
- Site information and subject details can be found in the available BBIR documents.
- Ahmed Alshareef's paper titled "Integrating Linear Viscoelastic Material Properties Derived from Magnetic Resonance Elastography into Subject-Specific Brain Models" appears in Brain Multiphysics. (doi)
- Ahmed Alshareef presented "Integrating Linear Viscoelastic Material Properties Derived from Magnetic Resonance Elastography into Subject-Specific Finite Element Brain Models" at the Biomedical Engineering Society (BMES) Annual Meeting, Orlando, FL, October 6-9, 2021.
- Jerry L. Prince delivered a keynote at the DALI MICCAI Workshop.
- Samuel W. Remedios presented "Joint Image and Label Self-Super-Resolution" at the Simulation and Synthesis in Medical Imaging (SASHIMI 2021) in conjunction with the 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021), Strasbourg, France, September 27 – October 1, 2021. (doi)
- Jacob C. Reinhold presented "A Structural Causal Model for MR Images of Multiple Sclerosis" at the 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021), Strasbourg, France, September 27 – October 1, 2021. (doi)
- Lianrui Zuo's paper titled "Unsupervised MR harmonization by learning disentangled representations using information bottleneck theory" appears in NeuroImage. (doi)
- Yufan He successfully defends his thesis titled "Retinal OCT Image Analysis Using Deep Learning".
- A paper on our Brain Biomechanics project titled "MR imaging of human brain mechanics in vivo: new measurements to facilitate the development of computational models of brain injury" appears in Annals of Biomedical Engineering. (doi)
- Yufan He's paper titled "Autoencoder Based Self-Supervised Test-Time Adaptation for Medical Image Analysis" appears in Medical Image Analysis. (doi)
- Congratulations to Lianrui Zuo on winning the Best Poster Award at the 27th Conference on Information Processing in Medical Imaging (IPMI 2021), Virtually in Bornholm, Denmark, June 28 - July 2, 2021.
- IACL papers at the 27th Conference on Information Processing in Medical Imaging (IPMI 2021), Virtually in Bornholm, Denmark, June 28 - July 2, 2021.
- IACL papers at the 18th IEEE International Symposium on Biomedical Imaging (ISBI 2021), Nice, France, April 13-16, 2021.
- Can Zhao's paper titled "SMORE: A Self-supervised Anti-aliasing and Super-resolution Algorithm for MRI Using Deep Learning" appears in IEEE Trans. on Medical Imaging. (doi)
- IACL members papers from the Proceedings of SPIE Medical Imaging (SPIE-MI 2021), San Diego, CA, February 14–18, 2021.
- ShangXian Wang presented "Thalamus Segmentation Using Convolutional Neural Network". (doi)
- Mallika Singh presented "Accurate Estimation of Total Intracranial Volume in MRI using a Multi-tasked Image-to-Image Translation Network". (doi)
- Di Liu presented "Label super resolution for 3D Magnetic Resonance Images using Deformable U-net". (doi)
- Muhan Shao presented "Reconstruction and refinement of crossing muscle fibers in the human tongue". (doi)
- Muhan Shao presented "Dynamic palatogram generation from Cine MRI for normalized speech assessment". (doi)
- Jerry L. Prince presented the Medical Imaging keynote at NeurIPS "New Approaches for Magnetic Resonance Image Harmonization", the video is now on YouTube .