Automated tracking of the mitral valve annulus motion in apical echocardiographic images using multidimensional dynamic programming.

We developed a semiautomatic method for tracking the mitral valve annulus (MVA) in echocardiographic images, in particular, tracking the septal and the lateral mitral valve hinge points. The algorithm is based on multidimensional dynamic programming combined with apodized block matching. The method was tested on single-beat apical four chamber image sequences of 20 patients with acute myocardial infarction. The automated tracking results were evaluated by comparing them with the average manual tracking results of two experts. The mitral valve hinge point displacements and the total mitral excursions obtained by the automatic technique agreed well with those obtained manually and outperformed two commonly used tracking methods (forward tracking and minimum tracking). In conclusion, this novel semiautomatic tracking method is clinically valuable and capable of tracking the MVA motion within the limits of interobserver variability. The technique is robust, even in low frame rate, redigitized VCR images of clinical quality.

Roentgen stereophotogrammetric analysis: an accurate tool to assess stent-graft migration.

PURPOSE: To evaluate in an in vitro model the feasibility and accuracy of Roentgen stereophotogrammetric analysis (RSA) versus computed tomography (CT) for the ability to detect stent-graft migration. METHODS: An aortic model was constructed from a 22-mm-diameter Plexiglas tube with 6-mm polytetrafluoroethylene inlays to mimic the renal arteries. Six tantalum markers were placed in the wall of the aortic tube proximal to the renal arteries. Another 6 markers were added to a Gianturco stent, which was cast in Plexiglas and placed inside the aorta and fixed to a micromanipulator to precisely control displacement of the stent along the longitudinal axis. Sixteen migrations were analyzed with RSA software and compared to the micromanipulator. Thirty-two migrations were measured by 3 observers from CT images acquired with 16x0.5-mm beam collimation and reconstructed with a 0.5-mm slice thickness and a 0.4-mm reconstruction interval. Measurements were made with Vitrea postprocessing software using a standard clinical protocol and central lumen line reconstruction. Results of CT were also compared to the micromanipulator. RESULTS: The mean RSA measurement error compared to the micromanipulator was 0.002+/-0.044 mm, and the maximum error was 0.10 mm. There was no statistically significant interobserver variability for CT (p=0.17). The pooled mean (maximum) measurement error of CT was 0.14+/-0.29 (1.00) mm, which was significantly different from the RSA measurement error (p<0.0001). CONCLUSION: Detection of endograft migration by RSA is feasible and was significantly more accurate than CT in this nonpulsatile in vitro model.

Modeling of scanning laser polarimetry images of the human retina for progression detection of glaucoma.

The development of methods to detect slowly progressing diseases is often hampered by the time-consuming acquisition of a sufficiently large data set. In this paper, a method is presented to model the change in images acquired by scanning laser polarimetry, for the detection of glaucomatous progression. The model is based on image series of 23 healthy eyes and incorporates colored noise, incomplete cornea compensation and masking by the retinal blood vessels. Additionally, two methods for detecting progression, taking either one or two follow-up visits into account, are discussed and tested on these simulated images. Both methods are based on Student's t-tests, morphological operations and anisotropic filtering. The images simulated by the model are visually pleasing, show corresponding statistical properties to the real images and are used to optimize the detection methods. The results show that detecting progression based on two follow-up visits greatly improves the sensitivity without adversely affecting the specificity.