Yousefi3, Mohamed S. Elmahdy3, Jeroen van Gemert2, Christophe Schülke1, Mariya Doneva1, Tim Nielsen1, Sergey Kastryulin1, Boudewijn P.F. Lelieveldt3, Matthias J.P. van Osch3, Marius Staring3 1 Philips Research 2 Philips Healthcare 3 Leiden University Medical Center FastMRI with Adaptive Intelligence Best performer in the FastMRI challenge (NeurIPS 2019) multi-coil 4x and 8x
Almost all MRI scanners use technique called “parallel imaging” that uses multiple Receiver coils in order to capture information from different spatial locations. This can speed up scanning process by ~2x.
Index Metric) measures the perceived change in structural information between two images. As with other quantitative metrics, may not capture qualitative differences perceived by radiologists. Stage 2 Top 4 entries as scored by SSIM are ranked by 7 radiologists. Winners determined by the best average radiologist ranking.
. " . Filtered-UNet • UNet-like design • Each feature map is filtered • Only basic DL operations to retain control • Convolution 2D without bias term • Leaky ReLU • Max pooling • Interpolation 2D • 2.5D Convolutions • Loss applied to the central slice only " . $ " . " .
within reach • Importance to involve Radiologist and Clinical Scientist • To design loss functions • To evaluate results • Importance of combining prior-knowledge in Deep- Learning solutions • Compressed sensing • MR Physics Paper from NeurIPS’19: https://arxiv.org/abs/1912.12259
Yousefi3, Mohamed S. Elmahdy3, Jeroen van Gemert2, Christophe Schülke1, Mariya Doneva1, Tim Nielsen1, Sergey Kastryulin1, Boudewijn P.F. Lelieveldt3, Matthias J.P. van Osch3, Marius Staring3 1 Philips Research 2 Philips Healthcare 3 Leiden University Medical Center Q&A