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. 2020 Nov 24;298(2):319–329. doi: 10.1148/radiol.2020201640

Figure 2:

Images demonstrate examples of model output for deep learning body composition pipeline. A, Examples of automated slice selection. The left CT slice was automatically selected by the model; the right CT slice was selected by a radiologist. Graph shows output of L3 regression model. Two vertical lines represent slices selected by radiologist (light blue) and by algorithm (orange). Dotted red line is unfiltered prediction; fluctuations in this curve correspond to adjacent vertebral levels. Zero crossing of filtered prediction is chosen as L3 level by algorithm (solid red line). B, Two examples of automated segmentation results, one per row. Left image shows automated segmentation by the model, the middle image is the input CT slice, and the right image is manually segmented ground truth produced by the radiologist. Color interpretation for segmentation masks are as follows: background or other, black; skeletal muscle, brown; subcutaneous fat, yellow; and visceral fat, white.

Images demonstrate examples of model output for deep learning body composition pipeline. A, Examples of automated slice selection. The left CT slice was automatically selected by the model; the right CT slice was selected by a radiologist. Graph shows output of L3 regression model. Two vertical lines represent slices selected by radiologist (light blue) and by algorithm (orange). Dotted red line is unfiltered prediction; fluctuations in this curve correspond to adjacent vertebral levels. Zero crossing of filtered prediction is chosen as L3 level by algorithm (solid red line). B, Two examples of automated segmentation results, one per row. Left image shows automated segmentation by the model, the middle image is the input CT slice, and the right image is manually segmented ground truth produced by the radiologist. Color interpretation for segmentation masks are as follows: background or other, black; skeletal muscle, brown; subcutaneous fat, yellow; and visceral fat, white.