Treatment-aware Diffusion Probabilistic Model for Longitudinal MRI Generation and Diffuse Glioma Growth Prediction

no code implementations • 11 Sep 2023 • Qinghui Liu, Elies Fuster-Garcia, Ivar Thokle Hovden, Donatas Sederevicius, Karoline Skogen, Bradley J MacIntosh, Edvard Grødem, Till Schellhorn, Petter Brandal, Atle Bjørnerud, Kyrre Eeg Emblem

In this paper, we present a novel end-to-end network capable of generating future tumor masks and realistic MRIs of how the tumor will look at any future time points for different treatment plans.

Decision Making Time Series +1

Handling Missing MRI Input Data in Deep Learning Segmentation of Brain Metastases: A Multi-Center Study

no code implementations • 27 Dec 2019 • Endre Grøvik, Darvin Yi, Michael Iv, Elizabeth Tong, Line Brennhaug Nilsen, Anna Latysheva, Cathrine Saxhaug, Kari Dolven Jacobsen, Åslaug Helland, Kyrre Eeg Emblem, Daniel Rubin, Greg Zaharchuk

A deep learning based segmentation model for automatic segmentation of brain metastases, named DropOut, was trained on multi-sequence MRI from 100 patients, and validated/tested on 10/55 patients.

Segmentation

MRI Pulse Sequence Integration for Deep-Learning Based Brain Metastasis Segmentation

no code implementations • 18 Dec 2019 • Darvin Yi, Endre Grøvik, Michael Iv, Elizabeth Tong, Kyrre Eeg Emblem, Line Brennhaug Nilsen, Cathrine Saxhaug, Anna Latysheva, Kari Dolven Jacobsen, Åslaug Helland, Greg Zaharchuk, Daniel Rubin

We illustrate not only the generalizability of the network but also the utility of this robustness when applying the trained model to data from a different center, which does not use the same pulse sequences.

Small Data Image Classification