GRAY IMAGE SKELETONIZATION WITH HOLLOW PREPROCESSING USING DISTANCE TRANSFORMATION

This paper presents a gray-scale skeletonization algorithm based on the gray weighted distance transformation (GWDT). The proposed algorithm is conceptually simple and could be used to process nonuniformly distributed gray-scale images. The algorithm can detect the hollows on the gray-scale image, a feature that is often ignored in other skeletonization algorithms, and improves the quality of the skeleton.

Assessing algorithms for defining vascular architecture in subharmonic images of breast lesions

The ability to accurately and non-invasively characterize breast lesions and their vasculature would greatly limit the number of unneeded biopsies performed annually. Subharmonic ultrasound imaging (SHI) allows exclusive imaging of vasculature in real time, while completely suppressing tissue signals. Previously, cumulative maximum intensity (CMI) projections of SHI data were shown to be useful for characterization, but lacked means of quantification. In this study we investigate three potential thinning algorithms for defining breast lesion architecture. Sequential thinning, parallel thinning, and distance transformation algorithms were compared using 40 in vitro test images. Sequential thinning was selected due to superior connectivity, minimal rotational variance, and sufficient data reduction. This algorithm was then applied to 16 CMI SHI images of breast lesions, out of which 13 were successfully skeletonized. Average bifurcations were 9.8 ± 8.18 and 6.9 ± 6.50 in malignant and benign lesions, respectively (p > 0.60). Average vessel-chain length was 88.9 ± 79.10 pixels versus 63.2 ± 45.65 pixels in malignant versus benign lesions (p > 0.40). While the sequential thinning algorithm was promising for quantifying breast vasculature, its ability to significantly differentiate between malignant and benign lesions in this study was limited by a high degree of variability and limited sample size.

Binary fingerprint image thinning using template-based PCNNs

This correspondence presents a coarse-to-fine binary-image-thinning algorithm by proposing a template-based pulse-coupled neural-network model. Under the control of coupled templates, this algorithm iteratively skeletonizes a binary image by changing the load signals of pulse neurons. A direction-constraining scheme for avoiding fingerprint ridge spikes has been discussed. Experiments show that this algorithm is effective for fingerprint thinning, as well as other common images. Moreover, this algorithm can be coupled with a fingerprint identification system to improve the recognition performance.

A new method of comprehensive static histomorphometry applied on human lumbar vertebral cancellous bone

The aim of the present study was to assess age-related changes in the human spine by use of established static histomorphometry, and to determine how these static histomorphometric measures are interrelated in human cancellous bone tissue. The material comprised normal human lumbar vertebral bodies (L-2) from 12 women (19-96 years) and 12 men (23-91 years) selected from a larger autopsy material to give an even age and gender distribution. In addition, L-2 from three female subjects (80, 88, and 90 years) with a known vertebral fracture of L-2 were considered. Approximately 9-mm-thick frontal (mediolateral) slices were embedded in methylmetacrylate, stained with aniline blue, and scanned into a computer with a flatbed image scanner at a high resolution (2400 dpi). With a custom-made computer program the following static histomorphometric measures were determined: trabecular bone volume; marrow space star volume; bone space star volume; anisotropy of bone and marrow phase (star length distribution method); node-strut analysis (node:terminus ratio); trabecular thickness; trabecular number; trabecular separation; and trabecular bone pattern factor. In addition, connectivity density was determined (by the ConnEulor method). All 11 histomorphometric measures, except bone space star volume and the two measures of anisotropy, showed a significant correlation with age. Marrow space star volume (r = 0.82) and trabecular bone volume (r = -0.81) showed the highest correlation with age. Furthermore, it was found that all of the histomorphometric measures were correlated, to different degrees. Trabecular bone volume correlated significantly with all ten histomorphometric measures, whereas the two anisotropy measures were poorly correlated to the other measures. Finally, we found the histomorphometric values in this study to be in excellent accordance with various previously published results from studies of human trabecular vertebral bone, the sole exception being marrow space star volume, which was probably due to the small (artificial) region of interest (ROI) that was used in the earlier studies. In conclusion, the new method applied herein allows for easy assessment of age-related changes and also for assessment of relationships between histomorphometric measures in human vertebral cancellous bone.

PARALLEL REDUCTION OPERATORS FOR GRAY-TONE PICTURES

Reduction operators iteratively applied to gray-tone pictures cause dilation of the regions, the gray-value of which is locally minimal, so that a gray-tone picture with no distinction between foreground and background is transformed into a set of bottom regions separated by ridge lines. The set of ridge lines can be understood as the skeleton of what is perceived as foreground. We describe a two-subiteration parallel skeletonization algorithm employing new reduction operators which are based on the nonridge point condition and are topology preserving. The performance of the algorithm is discussed, in particular with respect to certain critical configurations, and experimental work is reported to evaluate the thinning capability of the proposed reduction operators.