Ruler Based Automatic C-Arm Image Stitching Without Overlapping Constraint

Abstract

In this paper, we propose a new method for stitching multiple fluoroscopic images taken by a C-arm instrument. We employ an X-ray radiolucent ruler with numbered graduations while acquiring the images, and the image stitching is based on detecting and matching ruler parts in the images to the corresponding parts of a virtual ruler. To achieve this goal, we first detect the regular spaced graduations on the ruler and the numbers. After graduation labeling, for each image, we have the location and the associated number for every graduation on the ruler. Then, we initialize the panoramic X-ray image with the virtual ruler, and we "paste" each image by aligning the detected ruler part on the original image, to the corresponding part of the virtual ruler on the panoramic image. Our method is based on ruler matching but without the requirement of matching similar feature points in pairwise images, and thus, we do not necessarily require overlap between the images. We tested our method on eight different datasets of X-ray images, including long bones and a complete spine. Qualitative and quantitative experiments show that our method achieves good results.

Fig. 1

Pipeline of our method. For clarity, only two images are used in this example

Fig. 2

Image acquisition. Left the radiolucent X-ray ruler. Right example X-ray image taken with the ruler

Fig. 3

Graduation detection. a Main line detection. b Variation of image intensity along a line slightly above the main line. c The final result of graduation detection

Fig. 4

Number detection. a The training data for the 10 digits and a “bg” class. b Merging digits into numbers and labeling the closest graduations. c All the graduations are labeled with a corresponding number

Fig. 5

Qualitative results of image stitching on four datasets

Fig. 6

Clinical study setup (top image) and image stitching results for two clinical cases (bottom two images)