Student research accepted for presentation at IPMI 2017
CDT Student Razvan Marinescu has had a paper accepted at a leading international Conferernce.
Information Processing in Medical Imaging (IPMI) is a conference that focuses on novel developments in medical image acquisition and analysis. Today IPMI is widely recognized as a preeminent international forum for presentation of leading-edge research in the medical imaging field. The conference will take place in North Caroline, USA, 25-30 June 2017.
“A vertex clustering model for disease progression: Application to cortical thickness images”
We present a disease progression model with single vertex resolution that we apply to cortical thickness data. Our model works by clustering together vertices on the cortex that have similar temporal dynamics and building a common trajectory for vertices in the same cluster. The model estimates optimal stages and progression speeds for every subject. Simulated data show that it is able to accurately recover the vertex clusters and the underlying parameters. Moreover, our clustering model finds similar patterns of atrophy for typical Alzheimer’s disease (tAD) subjects on two independent datasets: the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and a cohort from the Dementia Research Centre (DRC), UK. Using a separate set of subjects with Posterior Cortical Atrophy (PCA) from the DRC dataset, we also show that the model finds different patterns of atrophy in PCA compared to tAD. Finally, our model also provides a novel way to parcellate the brain based on disease dynamics.
The image shows brain regions coloured according to how fast they are affected by Alzheimer’s disease. Regions most affected are coloured in red, representing a rapid decrease in cortical thickness, while regions least affected are coloured in blue, representing a slower decrease in cortical thickness. We show results for two diseases: (a-b) typical Alzheimer’s disease from two different datasets and © Posterior Cortical Atrophy. Figures d-f show the cortical thickness decline over time for each corresponding brain region.