14 research outputs found
Segmentation results.
<p>(a) the large tumor (2.532cc), auto-contours from intensity-based method (blue) and En-DeepMedic method (green) overlaid on physician drawn contour (red); (b) zoomed-in view of ROI in orange rectangle in (a); (c) the small tumor (0.537cc), auto-contours from En-DeepMedic method (green) overlaid on physician drawn contour (red); (d) zoomed-in view of ROI in orange rectangle in (c).</p
Comparison geometrical metric values of En-DeepMedic and intensity-based method on small- and large-size brain metastases tumors.
<p>Comparison geometrical metric values of En-DeepMedic and intensity-based method on small- and large-size brain metastases tumors.</p
The quantitative metrics of the En-DeepMedic with different local patch size.
<p>The quantitative metrics of the En-DeepMedic with different local patch size.</p
Box plots of geometrical metrics.
<p>(a) DCs, (b) MSSD, and (c) SDSSD of 5-fold cross validation with BRATS data using En-DeepMedic. The red line and cyan diamond inside each box denote medium value and mean value, respectively. The magenta star indicates the mean value of the geometrical metrics results from DeepMedic.</p
Segmentation results of Pt #2.
<p>(a) Segmentation of lesion in the left choroid plexus; (b): zoomed-in of the transverse view in (a).</p
Performance of DCs (±SD) in BRATS challenge 2015.
<p>Performance of DCs (±SD) in BRATS challenge 2015.</p
Process of 3D convolution layer.
<p>(a) 3D convolution of a feature map with a filter. (b) Generation of the <i>i</i>th feature map in the <i>l</i>th layer.</p
ROC curve of the En-DeepMedic with different local patch size.
<p>ROC curve of the En-DeepMedic with different local patch size.</p