Name
Abstract | ||
|---|---|---|
The problem of tumor growth prediction is challenging, but promising results have been achieved with both model-driven and statistical methods. In this work, we present a framework for the evaluation of growth predictions that focuses on the spatial infiltration patterns, and specifically evaluating a prediction of future growth. We propose to frame the problem as a ranking problem rather than a segmentation problem. Using the average precision as a metric, we can evaluate the results with segmentations while using the full spatiotemporal prediction. Furthermore, by applying a biophysical tumor growth model to 21 patient cases we compare two schemes for fitting and evaluating predictions. By carefully designing a scheme that separates the prediction from the observations used for fitting the model, we show that a better fit of model parameters does not guarantee a better predictive power.
|
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/978-3-031-08999-2_8 | Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries |
Keywords | DocType | ISSN |
Glioma, Growth model, Validation, Magnetic resonance imaging, Brain | Conference | 0302-9743 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Karin A. van Garderen | 1 | 0 | 0.34 |
| Sebastian R. van der Voort | 2 | 0 | 0.34 |
| Maarten M. J. Wijnenga | 3 | 0 | 0.34 |
| Fatih Incekara | 4 | 0 | 0.34 |
| Georgios Kapsas | 5 | 0 | 0.34 |
| Renske Gahrmann | 6 | 0 | 0.68 |
| Ahmad Alafandi | 7 | 0 | 0.34 |
| Marion Smits | 8 | 0 | 0.34 |
| Stefan Klein | 9 | 755 | 61.88 |