Prostate contours delineation using interactive directional active contours model and parametric shape prior model.

Prostate contours delineation on Magnetic Resonance (MR) images is a challenging and important task in medical imaging with applications of guiding biopsy, surgery and therapy. While a fully automated method is highly desired for this application, it can be a very difficult task due to the structure and surrounding tissues of the prostate gland. Traditional active contours-based delineation algorithms are typically quite successful for piecewise constant images. Nevertheless, when MR images have diffuse edges or multiple similar objects (e.g. bladder close to prostate) within close proximity, such approaches have proven to be unsuccessful. In order to mitigate these problems, we proposed a new framework for bi-stage contours delineation algorithm based on directional active contours (DAC) incorporating prior knowledge of the prostate shape. We first explicitly addressed the prostate contour delineation problem based on fast globally DAC that incorporates both statistical and parametric shape prior model. In doing so, we were able to exploit the global aspects of contour delineation problem by incorporating a user feedback in contours delineation process where it is shown that only a small amount of user input can sometimes resolve ambiguous scenarios raised by DAC. In addition, once the prostate contours have been delineated, a cost functional is designed to incorporate both user feedback interaction and the parametric shape prior model. Using data from publicly available prostate MR datasets, which includes several challenging clinical datasets, we highlighted the effectiveness and the capability of the proposed algorithm. Besides, the algorithm has been compared with several state-of-the-art methods.

Anatomical study of phrenic nerve using ultrasound.

PURPOSE: To demonstrate whether ultrasonography may allow a precise assessment of the course and relations of the phrenic nerve in its cervical portion. METHODS: This study, initially undertaken in five cadavers, was followed by high-resolution ultrasonographic study in 20 volunteers (40 nerves) by two radiologists in consensus. The location, course and relations of the phrenic nerve to the adjacent anatomical structures were analysed. RESULTS: The phrenic nerve could be nicely identified through the majority of its course by high-resolution ultrasonography. Useful anatomic landmarks for the detection of the nerve could be defined; these include the transverse cervical and ascending cervical arteries. Some anatomical variations were observed. CONCLUSION: Knowledge of the nerve's precise location, which may demonstrate individual variations, may have useful clinical applications.