27 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- The University of QueenslandAU4 papers
- Stanford UniversityUS3 papers
- Allen Institute for Cell ScienceUS2 papers
- ARC Centre of Excellence in Advanced Molecular ImagingAU2 papers
- Broad InstituteUS2 papers
- European Molecular Biology LaboratoryDE2 papers
- Frederick National Laboratory for Cancer ResearchUS2 papers
- Heidelberg UniversityDE2 papers
- KTH Royal Institute of TechnologySE2 papers
- La Trobe UniversityAU2 papers
- Monash UniversityAU2 papers
- National Institute of Standards and TechnologyUS2 papers
9 papers
Towards Determining Mechanical Properties of Brain-Skull Interface Under Tension and Compression
Sajjad Arzemanzadeh, Benjamin Zwick, Karol Miller +3
Computational biomechanics models of the brain have become an important tool for investigating the brain responses to mechanical loads. The geometry, loading conditions, and consti…
Enabling Global Image Data Sharing in the Life Sciences
Peter Bajcsy, Sreenivas Bhattiprolu, Katy Boerner +20
Coordinated collaboration is essential to realize the added value of and infrastructure requirements for global image data sharing in the life sciences. In this White Paper, we tak…
Harmonizing the Generation and Pre-publication Stewardship of FAIR Image Data
Nikki Bialy, Frank Alber, Brenda Andrews +44
Alongside molecular insights into genes and proteins, biological imaging holds great promise for deepening scientific understanding of complex cellular systems and advancing predic…
NeXtQSM -- A complete deep learning pipeline for data-consistent quantitative susceptibility mapping trained with hybrid data
Francesco Cognolato, Kieran O'Brien, Jin Jin +4
Deep learning based Quantitative Susceptibility Mapping (QSM) has shown great potential in recent years, obtaining similar results to established non-learning approaches. Many curr…
A comprehensive solution to retrieval-based chatbot construction
Kristen Moore, Shenjun Zhong, Zhen He +4
In this paper we present the results of our experiments in training and deploying a self-supervised retrieval-based chatbot trained with contrastive learning for assisting customer…
The Federated Tumor Segmentation (FeTS) Challenge
Sarthak Pati, Ujjwal Baid, Maximilian Zenk +29
This manuscript describes the first challenge on Federated Learning, namely the Federated Tumor Segmentation (FeTS) challenge 2021. International challenges have become the standar…
Accelerating Quantitative Susceptibility Mapping using Compressed Sensing and Deep Neural Network
Yang Gao, Martijn Cloos, Feng Liu +3
Quantitative susceptibility mapping (QSM) is an MRI phase-based post-processing method that quantifies tissue magnetic susceptibility distributions. However, QSM acquisitions are r…
A globally convergent algorithm for lasso-penalized mixture of linear regression models
Luke R. Lloyd-Jones, Hien D. Nguyen, Geoffrey J. McLachlan
Variable selection is an old and pervasive problem in regression analysis. One solution is to impose a lasso penalty to shrink parameter estimates toward zero and perform continuou…
Spatial Clustering of Time-Series via Mixture of Autoregressions Models and Markov Random Fields
Hien D Nguyen, Geoffrey J McLachlan, Jeremy F P Ullmann +1
Time-series data arise in many medical and biological imaging scenarios. In such images, a time-series is obtained at each of a large number of spatially-dependent data units. It i…