Segmentation of Bone Vessels in 3D Micro-CT Images Using the Monogenic Signal Phase and Watershed

We propose an algorithm based on marker-controlled watershed and the monogenic signal phase asymmetry for the segmentation of bone and micro-vessels in mouse bone. The images are acquired using synchrotron radiation micro-computed tomography ( $\text{SR}-\mu \text{CT}$ ). The marker image is generated with hysteresis thresholding and morphological filters. The control surface is generated using the phase asymmetry of the monogenic signal in order to detect edge-like structures only, as well as improving detection in low contrast areas, such as bone-vessel interfaces. The quality of segmentation is evaluated by comparing to manually segmented images using the Dice coefficient. The proposed method shows substantial improvement compared to a previously proposed method based on hysteresis thresholding, as well as compared to watershed using the gradient image as control surface. The algorithm was applied to images of healthy and metastatic bone, permitting quantification of both bone and vessel structures.