Learner Profiles

Ayla from Cancer Center

Ayla is an MD, PhD candidate in the department of hematology at a major academic medical center. She began working on data from pediatric thalassemia patients with the question of how the disease affects brain development. She was given tabular data on patients’ brain measurements, based on many brain MRIs collected during the study of these patients, as well as patients of the same age without thalassemia. But these brain MRIs were collected from different institutions. She seeks to figure out whether the tabular data produced make sense and to remove MRIs that were acquired incorrectly. Then she would like to use machine learning or deep learning to determine whether thalassemia implies specific changes in patients’ brains. She is unsure how to deal with different collection sites.

Lenoard from Radiology

Lenoard, a PhD candidate at an academic medical center, is excited to dig deeper into the complexities of diagnostic image processing. He is particularly intrigued by the algorithmic complexities of image processing pipelines and seeks guidance on maximizing efficiency and scalability in handling large datasets. In addition, Lenoard is interested in exploring dimensionality reduction and image segmentation techniques, including recent advances and their practical implications. He is also interested in working with 3D meshes and wishes to learn the basics of synthetic image generation and resolution enhancement, despite his limited familiarity with medical imaging applications, which he is eager to understand better.

Dahlia from Pathology

Dahlia is a PhD candidate in pathology at a major academic medical center. She wants to examine the effect of hormone levels on bones and bone strength. She has many CT scans, where an algorithm has screened for osteoporosis using the vertebral body, but she is trying to understand the links between hormones and actual bone architecture. She wants to understand what radiometric parameters correlate to osteoporosis, so she can build more explainable models.

Dan from Technical Medicine

Dan is a postdoctoral researcher in technical medicine working at a major academic medical center. He is helping to build a new pipeline for pediatric MRI volume measurement. This involves image registration to a pediatric brain atlas, but unfortunately none of the popular open tools perform this task on very young children. Dan needs to build the new tool that will segment and then register pediatric brains to an existing atlas.