Figure 3
From: Fully automated kidney image biomarker prediction in ultrasound scans using Fast-Unet++
Post-processing of axial view image. (a) Segmentation of axial image, (b) rotation of the image to make it horizontal, (c) estimating kidney thickness (KT) by finding two terminal points, (d) separation of upper and lower parts of the mask and finding the longest distance, (e) kidney width (KW) and KT, and (f) KW and KT in the original image.
