Robustness and accuracy of feature-based single image 2-D-3-D registration without correspondences for image-guided intervention.

2-D-to-3-D registration is critical and fundamental in image-guided interventions. It could be achieved from single image using paired point correspondences between the object and the image. The common assumption that such correspondences can readily be established does not necessarily hold for image guided interventions.

Physiology and cell biology of acupuncture observed in calcium signaling activated by acoustic shear wave.

This article presents a novel model of acupuncture physiology based on cellular calcium activation by an acoustic shear wave (ASW) generated by the mechanical movement of the needle. An acupuncture needle was driven by a piezoelectric transducer at 100 Hz or below, and the ASW in human calf was imaged by magnetic resonance elastography. At the cell level, the ASW activated intracellular Ca(2+) transients and oscillations in fibroblasts and endothelial, ventricular myocytes and neuronal PC-12 cells along with frequency-amplitude tuning and memory capabilities.

Vessel extraction under non-uniform illumination: a level set approach.

Vessel extraction is one of the critical tasks in clinical practice. This communication presents a new approach for vessel extraction using a level-set-based active contour by defining a novel local term that takes local image contrast into account. The proposed model not only preserves the performance of the existing models on blurry images, but also overcomes their inability to handle nonuniform illumination.

A novel active contour model using local and global statistics for vessel extraction.

Vessel extraction is one of the critical tasks in clinical practice. Most of the deformable models used in these applications are based on either image gradient or global statistics of the intensity as their curve evolution and stopping criteria. However, the models using global statistic alone are not adaptive to the uneven intensity distribution since they do not take local variations in the area of interest into consideration.

An efficient parameterless quadrilateral-based image segmentation method.

This paper proposes a general quadrilateral-based framework for image segmentation, in which quadrilaterals are first constructed from an edge map, where neighboring quadrilaterals with similar features of interest are then merged together to form regions. Under the proposed framework, the quadrilaterals enable the elimination of local variations and unnecessary details for merging from which each segmented region is accurately and completely described by a set of quadrilaterals. To illustrate the effectiveness of the proposed framework, we derived an efficient and high-performance parameterless quadrilateral-based segmentation algorithm from the framework.