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Lecture Notes in Computer Science
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 findsdoi:10.1007/978-3-319-59050-9_11 fatcat:nkxw7qrlfffrfesdgobwjqcnxa