Marilyn E. Noz

Model studies on segmental movement in lumbar spine using a semi-automated program for volume fusion.

Objective: To validate a new non-invasive CT method for measuring segmental translations in lumbar spine in a phantom using plastic vertebrae with tantalum markers and human vertebrae. Material and Methods: One hundred and four CT volumes were acquired of a phantom incorporating three lumbar vertebrae. Lumbar segmental translation was simulated by altering the position of one vertebra in all three cardinal axes between acquisitions. The CT volumes were combined into 64 case pairs, simulating lumbar segmental movement of up to 3 mm between acquisitions. The relative movement between the vertebrae was evaluated visually and numerically using a volume fusion image post-processing tool. Results were correlated to direct measurements of the phantom. Results: On visual inspection, translation of at least 1 mm or more could be safely detected and correlated with separation between the vertebrae in three dimensions. There were no significant differences between plastic and human vertebrae. Numerically, the accuracy limit for all the CT measurements of the 3D segmental translations was 0.56 mm (median: 0.12; range: −0.76 to +0.49 mm). The accuracy for the sagittal axis was 0.45 mm (median: 0.10; range: −0.46 to +0.62 mm); the accuracy for the coronal axis was 0.46 mm (median: 0.09; range: −0.66 to +0.69 mm); and the accuracy for the axial axis was 0.45 mm (median: 0.05; range: −0.72 to + 0.62 mm). The repeatability, calculated over 10 cases, was 0.35 mm (median: 0.16; range: −0.26 to +0.30 mm). Conclusion: The accuracy of this non-invasive method is better than that of current routine methods for detecting segmental movements. The method allows both visual and numerical evaluation of such movements. Further studies are needed to validate this method in patients.

Standardizing the Raster display for medical images using a fixed set of frame buffer primitives

Two major difficulties associated with medical image processing are the diverse image formats that must be dealt with because of the differences in image sources and the number of incompatible display systems available for viewing images both before and after processing. We describe a very small set of primitives that need to be defined to utilize any raster display. When these primitives have been implemented for a particular device, then a standard set of image display programs can be compiled and images and the results of image processing can be displayed. The main purpose of this paper is to describe what a raster display looks like from the point of view of the programmer and to define the specific hardware and software data about the raster display that must be known in order to implement the small set of primitives.