Multi-Coil MRI Reconstruction Challenge-Assessing Brain MRI Reconstruction Models and Their Generalizability to Varying Coil Configurations.

Deep-learning-based brain magnetic resonance imaging (MRI) reconstruction methods have the potential to accelerate the MRI acquisition process. Nevertheless, the scientific community lacks appropriate benchmarks to assess the MRI reconstruction quality of high-resolution brain images, and evaluate how these proposed algorithms will behave in the presence of small, but expected data distribution shifts. The multi-coil MRI (MC-MRI) reconstruction challenge provides a benchmark that aims at addressing these issues, using a large dataset of high-resolution, three-dimensional, T1-weighted MRI scans. The challenge has two primary goals: (1) to compare different MRI reconstruction models on this dataset and (2) to assess the generalizability of these models to data acquired with a different number of receiver coils. In this paper, we describe the challenge experimental design and summarize the results of a set of baseline and state-of-the-art brain MRI reconstruction models. We provide relevant comparative information on the current MRI reconstruction state-of-the-art and highlight the challenges of obtaining generalizable models that are required prior to broader clinical adoption. The MC-MRI benchmark data, evaluation code, and current challenge leaderboard are publicly available. They provide an objective performance assessment for future developments in the field of brain MRI reconstruction.

"Hands-On, Minds-On, and Science-Up": A Concept-Based Learning Laboratory With a Taste of Research Experience for an Undergraduate Biomedical Engineering Course.

In this paper, we bridged faculty research expertise with concept-based learning pedagogy to design and implement a unique laboratory experience for biomedical engineering undergraduate students enrolled in the biomechanics of tissues course at the University of Calgary. This laboratory aimed to increase student engagement, facilitate deeper understanding of course content, and provide an opportunity for accelerated undergraduate research through "hands-on," "minds-on," and "science-up" learning components, respectively. The laboratory exercise involves testing aortic tissues using a novel miniaturized planar biaxial machine. This type of machine is normally reserved for use in the context of research. The relevance of the proposed laboratory as a teaching tool was assessed using student feedback. Results indicate an overall valuable and positive learning experience for students.