Minimizing the total service time of discrete dynamic berth allocation problem by an iterated greedy heuristic.

Berth allocation is the forefront operation performed when ships arrive at a port and is a critical task in container port optimization. Minimizing the time ships spend at berths constitutes an important objective of berth allocation problems. This study focuses on the discrete dynamic berth allocation problem (discrete DBAP), which aims to minimize total service time, and proposes an iterated greedy (IG) algorithm to solve it. The proposed IG algorithm is tested on three benchmark problem sets. Experimental results show that the proposed IG algorithm can obtain optimal solutions for all test instances of the first and second problem sets and outperforms the best-known solutions for 35 out of 90 test instances of the third problem set.

Artifact-resistant superimposition of digital dental models and cone-beam computed tomography images.

PURPOSE: Combining the maxillofacial cone-beam computed tomography (CBCT) model with its corresponding digital dental model enables an integrated 3-dimensional (3D) representation of skeletal structures, teeth, and occlusions. Undesired artifacts, however, introduce difficulties in the superimposition of both models. We have proposed an artifact-resistant surface-based registration method that is robust and clinically applicable and that does not require markers. MATERIALS AND METHODS: A CBCT bone model and a laser-scanned dental model obtained from the same patient were used in developing the method and examining the accuracy of the superimposition. Our method included 4 phases. The first phase was to segment the maxilla from the mandible in the CBCT model. The second phase was to conduct an initial registration to bring the digital dental model and the maxilla and mandible sufficiently close to each other. Third, we manually selected at least 3 corresponding regions on both models by smearing patches on the 3D surfaces. The last phase was to superimpose the digital dental model into the maxillofacial model. Each superimposition process was performed twice by 2 operators with the same object to investigate the intra- and interoperator differences. All collected objects were divided into 3 groups with various degrees of artifacts: artifact-free, critical artifacts, and severe artifacts. The mean errors and root-mean-square (RMS) errors were used to evaluate the accuracy of the superimposition results. Repeated measures analysis of variance and the Wilcoxon rank sum test were used to calculate the intraoperator reproducibility and interoperator reliability. RESULTS: Twenty-four maxilla and mandible objects for evaluation were obtained from 14 patients. The experimental results showed that the mean errors between the 2 original models in the residing fused model ranged from 0.10 to 0.43 mm and that the RMS errors ranged from 0.13 to 0.53 mm. These data were consistent with previously used methods and were clinically acceptable. All measurements of the proposed study exhibited desirable intraoperator reproducibility and interoperator reliability. Regarding the intra- and interoperator mean errors and RMS errors in the nonartifact or critical artifact group, no significant difference between the repeated trials or between operators (P < .05) was observed. CONCLUSIONS: The results of the present study have shown that the proposed regional surface-based registration can robustly and accurately superimpose a digital dental model into its corresponding CBCT model.

Registration of micro-computed tomography and histological images of the guinea pig cochlea to construct an ear model using an iterative closest point algorithm.

We present a practical and systematic method to reconstruct accurate physical models of the guinea pig ear (n = 1). The method uses a semi-automatic technique to create three-dimensional (3-D) models of the guinea pig cochlea by registration of micro-computed tomography (CT) and histological images. An iterative closest point algorithm was employed to minimize the sum of square errors with respect to the closest histological model and corresponding micro-CT model. This allowed creation of an accurate geometric ear model including external ear canal, tympanic membrane, middle ear cavity, auditory ossicles, and the cochlea. The characteristic cross-sectional areas of scala tympani, scala vestibuli, and scala media were measured. The length, thickness, and apex width of the guinea pig's basilar membrane were compared to the data found in literature. Some shape parameters were also compared among different species. The results confirmed that the geometric model created by this method was accurate. This method provides an effective way to visualize the 3-D structure and the detailed information about ear geometry required for finite element and multibody dynamic analysis.

Symmetric region growing.

Of the many proposed image segmentation methods, region growing has been one of the most popular. Research on region growing, however, has focused primarily on the design of feature measures and on growing and merging criteria. Most of these methods have an inherent dependence on the order in which the points and regions are examined. This weakness implies that a desired segmented result is sensitive to the selection of the initial growing points. We define a set of theoretical criteria for a subclass of region-growing algorithms that are insensitive to the selection of the initial growing points. This class of algorithms, referred to as symmetric region growing algorithms, leads to a single-pass region-growing algorithm applicable to any dimensionality of images. Furthermore, they lead to region-growing algorithms that are both memory- and computation-efficient. Results illustrate the method's efficiency and its application to 3D medical image segmentation.

Multi-generational analysis and visualization of the vascular tree in 3D micro-CT images.

Micro-CT scanners can generate large high-resolution three-dimensional (3D) digital images of small-animal organs, such as rat hearts. Such images enable studies of basic physiologic questions on coronary branching geometry and fluid transport. Performing such an analysis requires three steps: (1) extract the arterial tree from the image; (2) compute quantitative geometric data from the extracted tree; and (3) perform a numerical analysis of the computed data. Because a typical coronary arterial tree consists of hundreds of branches and many generations, it is impractical to perform such an integrated study manually. An automatic method exists for performing step (1), extracting the tree, but little effort has been made on the other two steps. We propose an environment for performing a complete study. Quantitative measures for arterial-lumen cross-sectional area, inter-branch segment length, branch surface area and others at the generation, inter-branch, and intra-branch levels are computed. A human user can then work with the quantitative data in an interactive visualization system. The system provides various forms of viewing and permits interactive tree editing for "on the fly" correction of the quantitative data. We illustrate the methodology for 3D micro-CT rat heart images.