Cylindrical depth image based customized helical bone plate design.

Commercial straight metal plates have been generally used to fix fractured bones, but recently, the need for customized and helical metal plates has emerged. Customized metal plates are designed to fit the shape of the fracture area that is a 3D curved surface, making it more difficult than designing on a 2D plane. Helical plates are researched due to their advantage in avoiding blood vessel damage compared to commercially available straight metal plates. In this paper, we propose a novel algorithm to design a customized helical metal plate for the femur using cylindrical depth images and Boolean operations. We also present the results of 3D printing a metal plate designed using the proposed algorithm, and the shape matching is verified by calculating the minimum distance between the surface of the printed plate and the surface of the femur.

A target model construction algorithm for robust real-time mean-shift tracking.

Mean-shift tracking has gained more interests, nowadays, aided by its feasibility of real-time and reliable tracker implementation. In order to reduce background clutter interference to mean-shift object tracking, this paper proposes a novel indicator function generation method. The proposed method takes advantage of two 'a priori' knowledge elements, which are inherent to a kernel support for initializing a target model. Based on the assured background labels, a gradient-based label propagation is performed, resulting in a number of objects differentiated from the background. Then the proposed region growing scheme picks up one largest target object near the center of the kernel support. The grown object region constitutes the proposed indicator function and this allows an exact target model construction for robust mean-shift tracking. Simulation results demonstrate the proposed exact target model could significantly enhance the robustness as well as the accuracy of mean-shift object tracking.

Structural identification of modified amino acids on the interface between EPO and its receptor from EPO BRP, human recombinant erythropoietin by LC/MS analysis.

Protein modifications of recombinant pharmaceuticals have been observed both in vitro and in vivo. These modifications may result in lower efficacy, as well as bioavailability changes and antigenicity among the protein pharmaceuticals. Therefore, the contents of modification should be monitored for the quality and efficacy of protein pharmaceuticals. The interface of EPO and its receptor was visualized, and potential amino acids interacting on the interface were also listed. Two different types of modifications on the interface were identified in the preparation of rHu-EPO BRP. A UPLC/Q-TOF MS method was used to evaluate the modification at those variants. The modification of the oxidized variant was localized on the Met54 and the deamidated variants were localized on the Asn47 and Asn147. The extent of oxidation at Met54 was 3.0% and those of deamidation at Asn47 and Asn147 were 2.9% and 4.8%, respectively.

Boundary detection in carotid ultrasound images using dynamic programming and a directional Haar-like filter.

The intima-media thickness (IMT) of the carotid artery, obtained from B-mode ultrasound images, has recently been proposed as one of the most useful indices of atherosclerosis and can also be used to predict major cardiovascular events. Ultrasonic measurements of the IMT are conventionally obtained by time-consuming manual tracing of the interfaces between tissue layers. We propose a computerized method to detect the boundary of the intima-media complex using a directional Haar-like filter that can account for the slope of the boundary in an image. The directional Haar-like filter extracts a directional boundary feature as an image feature in the region of interest, which is used to compute a cost function. A cost function includes not only the directional Haar-like filtering value but also the geometric continuity that is computed for every pixel in the region of interest. The optimal boundary pixels are detected by using a dynamic programming approach that searches for the pixel that minimizes the cost function in each column of the image. We compared the performance of the proposed method with that of manual methods performed by two radiologists. The results showed that our approach produces very similar results to those based on manual tracing, and there was no statistically significant difference between the IMT measurements segmented manually and those analyzed using our method.

Adaptive reconstruction of pipe-shaped human organs from 3D ultrasonic volume.

In this paper, we introduce an adaptive scheme for reconstructing pipe-shaped human organs from the volume data acquired by 3D ultrasonic devices. No other methods but the contour-based scheme was used in the process of reconstructing the volume data into a 3D polygonal surface. In the first step, the algorithm extracts contours from the sampled slices of the volume data using the modified radial gradient method, in which the points are sampled on the boundary of the region of interest by radiating rays and connected through making use of the chain code algorithm. The contours are represented as the context-free grammar, and their parsing trees are traversed during the reconstruction. The generated polygonal surface is refined as the contours are being refined at the casting of the new rays between the existing rays to sample new points and to modify the contours according to these newly derived points. An adaptive scheme is achieved in casting the rays adaptively on the slices. The proposed algorithm is to be applied in reconstructing the pipe-shaped human organs, such as arteries or blood vessels, to a polygonal surface. In this paper, we present an innovative tiling algorithm that reconstructs pipe-shaped human organ from 3D ultrasonic datasets. A set of contours on slices through the ultrasonic datasets is extracted using a modified radial gradient method, and our algorithm tiles these to make a polygonal surface. The tiling is performed by traversing a set of parsing trees which represent the contours in a context-free grammar. This makes our algorithm more efficient than previous algorithms that reconstruct surfaces from a set of contours. The first step of the algorithm is to determine a contour on each slice of the 3D ultrasonic dataset. After removing unwanted artifacts from the slice by applying several noise-removing operators, the centroid pixel of region of interest on the slice is designated. A radial gradient method casts a set of rays from the centroid pixel to the boundary of the slice and computes the intersection points between the rays and the boundary cells of the object so as to determine the contours. The second step uses context-free grammar that represents the contours. Each edge of a contour can be classified into six categories according to its relation with the rays cast from the centroid pixel, and the contour can then be represented by a string in a context-free grammar whose terminal symbols are the six types of the edges. A polygonal surface between two contours is constructed by traversing the parsing trees of the contours and determining the corresponding edges. The third step is to refine the smooth surface constructed in the second step by casting more rays. Additional rays refine the contour by decomposing the edges on the contour and convert leaf node of the parsing tree to the root of a new sub-tree whose leaf nodes denote the newly created edges. Our algorithm was tested on a phantom object and an artery from the neck. Results show that the performance of the algorithm and the quality of the resulting surface are better than those of existing algorithms. We have implemented a navigation facility that allows users to investigate the pipe-shaped human organs interactively.