Motion compensation of ultrasonic perfusion images
Summary (2 min read)
1. INTRODUCTION
- 2D ultrasonography (US) is one of the most widely used medical imaging techniques.
- 5 During 2D contrast enhanced US (CEUS) examinations studying perfusion, the sonographer normally holds the probe still in a particular position and orientation to image a suitable slice of tissue of interest during CA administration.
- While this motion can normally be interpreted by well trained physicians,6 in computer-assisted analysis the different image frames of a time-dependent acquisition are required to be kept aligned in order to extract valid perfusion parameters over time.
- The acquisition usually produces two parallel image sequences: standard b-mode∗ and the measured CA enhancement (Fig. 1).
- Therefore, a statistically based Markov Random Field (MRF) segmentation7 of the b-mode sequence is used to produce feature images which are less subject to noise influence over time.
3. METHOD
- The registration procedure consists of four main steps (Fig. 2).
- After each iteration the global energy, consisting of the sum of Elocal for all sites in the image, is calculated.
- The difference images indicate a higher accordance using the label map and a lower risk of arbitrary dissimilarity due to noise.
- The goal is to remove coarse motion influence, mainly caused by extrinsic motion influence and patient breathing, with translation and rotation (rigid transformations) and the remaining non-linear motion with B-Spline controlled transformations with a 8× 8 point grid (Fig. 4c, 4f).
- The transformation parameters of each frame registration are initialized with the final transformation parameters from the preceding frame for reasons of stability and efficiency.
4. RESULTS AND DISCUSSION
- For evaluation, three data sets showing the intestinal wall have been used with a spatial resolution ranging between 200 and 500 pixels in x- and y-direction and a temporal resolution between 350 and 1000 frames (≈ 10 frames per second for b-mode and contrast sequence, respectively).
- To measure the quality of the registration result, two experiments have been performed.
- In their opinion this should be a first indicator of improved contrast signal correspondence over time, although this signal is still disturbed by noise and speckle artifacts and thus contains enough potential to distort the time course of contrast enhancement.
- The perfusion curve smoothness measured after intensity-based registration marginally improved by 0.6%, for label map-based without MRF prior by 0.5% and with MRF prior enabled it could be improved by 1.9%.
- In dataset 3 the intestinal area (Fig. 5a) has very little variation resulting in a large label area in the label map (Fig. 5b, 5c).
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Frequently Asked Questions (2)
Q2. What have the authors stated for future works in "Motion compensation of ultrasonic perfusion images" ?
As future work the authors plan to update the label map at each evaluation step of transformation parameters. Within this context it should be considered if the calculation of the transformation parameters can be performed simultaneously for all time steps11 or within a reasonable temporal area so that temporal constraints can be incorporated to achieve smooth transitions over time.