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We propose a navigation-based computer aided diagnosis (CAD) system for the colon. When diagnosing the colon using virtual colonoscopy (VC), a physician makes a diagnosis by navigating (flying-through) the colon. However, the viewpoints and the viewing directions must be changed many times because the colon is a very long and winding organ with many folds. This is a time-consuming task for physicians. We propose a new navigation-based CAD system for the colon providing virtual unfolded (VU) views, which enables physicians to observe a large area of the colonic wall at a glance. This system generates VU, VC, and CT slice views that are perfectly synchronized. Polyp candidates, which are detected automatically, are overlaid on them. We applied the system to abdominal CT images. The experimental results showed that the system effectively generates VU views for observing colon regions.

This paper proposes a thinning algorithm for tracking ridge lines in three-dimensional (3D) gray images. A characteristic of this algorithm is that input 3D gray images can be used directly without preprocessing such as binarization or separation of background. This algorithm obtains thin lines by tracking ridge lines, starting at points where the intensity has its local maximum. Combinations of three principal curvatures of a 4D hypersurface are used for the condition of continuation of tracking. It has been verified that lines considered to be ridge lines can be extracted when the proposed algorithm is applied to artificial images and real images. © 2001 Scripta Technica, Syst Comp Jpn, 32(12): 25–37, 2001 [ABSTRACT FROM AUTHOR]

In this paper, thinning algorithms considering the density of three-dimensional (3D) images are proposed and their characteristics are defined. In the 3D thinning methods reported so far, only two-level images which could not use the density information have been treated. Moreover, they are adversely influenced by noise in the shape of the objects. The proposed method can apply a thinning algorithm not only to the shape information but also to the density information. We apply this method to artificial objects and to real blood vessel area images extracted from 3D CT images; we then compare our results with the results of the conventional thinning methods applied to binary images and evaluate them qualitatively as well as quantitatively. It is shown that if we apply our thinning technique suitably with allowance for density information, then the influence of shape noise can be made smaller and natural thinning results can be obtained. © 1997 Scripta Technica, Inc. Syst Comp Jpn, 28(9): 55–66, 1997 [ABSTRACT FROM AUTHOR]

This paper proposes a segmentation method based on region information and edge information. The method consists of three steps: (1) a connected component which is a pan of an object is extracted as a seed by using a simple process such as a histogram analysis; (2) this seed is expanded repeatedly, and (3) to evaluate the possibility of the expansion, the uniformity of gray levels (region information) and checking me presence of border pixels (edge information) are used. Although the method can be considered as a kind of region expansion, the significant features are that it contains the growth of a seed and the edge information (a part of control information) to expand the region repeatedly. The former gives preliminary information on approximate gray levels of an object and extracts the object as a connected component, and the Inner makes the edge information more useful. Although the usefulness of the edge information in a conventional region-and-edge integrated method such as the superslice algorithm depends greatly on its region segmentation, the use of such methods can be avoided in the proposed method, since both the region and edge information are used simultaneously for the control conditions of the region expansion. The method is justified experimentally by using synthetic images and actual images in two and three dimensions. [ABSTRACT FROM AUTHOR]

This paper proposes a method of decomposing a D- figure based on the distance features of the figure. This method, called breaking where it can be broken," can be applied to digital figures of arbitrary dimension and is designed to produce the familiar decomposition which corresponds to the physical image when the rigid body has a weakness in its figure. When the information available about the digital picture is black-and-white, the decomposition of the figure must be based only on topological properties such as 1-pixel connectivity, construction of a good figure decomposition is difficult because of the limited information. First, the definition of the decomposition of a D- figure is given. Then the algorithm which realizes it in the digital space is presented. Finally, the results of experiments with the two-dimensional (2-C)) D-figure decomposition of artificial figures are given and the usefulness of this method is illustrated with a practical example, the analysis of a 3-D D-figure of a medical picture. [ABSTRACT FROM AUTHOR]

This paper proposes a variable neighborhood distance transformation algorithm for two- and three-dimensional (2-D and 3-D) digital binary pictures which is based on a new concept called path extension. The properties and performance of the method are experimentally evaluated. An algorithm was constructed using path extension which calculates the variable neighborhood distance for all one pixels in a 2-D picture, using a sequence of four and eight neighborhoods composed in an appropriate way. In previous distance transformation algorithms, the distance for the central pixel under consideration is calculated uniquely from the distances of several neighborhood pixels, while the distance transformation in the path extension algorithm is executed by determining the distances of several neighborhood pixels from the distance of the central pixel under consideration. This paper proposes a serial path extension algorithm and two parallel path extension algorithms for both 2-D and 3-D pictures. For comparison of performance, one serial and one parallel algorithm, which are modifications of the traditional fixed neighborhood algorithms, are further analyzed. Finally, the results of an experimental evaluation are presented for computation time in the five proposed algorithms. [ABSTRACT FROM AUTHOR]

This paper presents basic concepts and fundamental algorithms for processing three- dimensional digitized images (3D images). A 3D image is a pictorial datum obtained by measuring physical quantities distributed at every point in 3D space and arranging the measurements on a 3D array. First, we present several basic concepts concerning geometrical properties of 3D images, which include connectivity, the connected component, the Euler number, and deletability. Then we explain outlines of basic algorithms derived by using the forementioned concepts based on research results by the authors' group. Procedures referred to here are as follows: calculation of the Euler number, deletability test of 1-voxels, shrinking, thinning, and border following. Finally, we add 51 refer- ences which may aid more detailed research; these references also will supplement the brief explanations and small number of procedures we are limited to in this article. [ABSTRACT FROM AUTHOR]

This paper discusses the structural analysis algorithm for line patterns, based on the distance transformation of a line pattern by iterative local parallel processing. Although parallel processors have been applied recently to image processing, the processing of line patterns in the past was based primarily on the transformation of the object pattern into the list structure or symbol strings. Few studies have been made on the parallel processing algorithm for a line pattern. From such a viewpoint, this paper presents parallel-type algorithms for loop counting, loop extraction and arc decomposition, among the procedures for processing line patterns. Properties of these algorithms also are discussed. The method proposed here is based on the distance transformation (Min. type) for line patterns we developed, and can be performed by iterative local parallel processing, in the same way as the distance transformation itself. [ABSTRACT FROM AUTHOR]

The median filter is used frequently in image processing for smoothing while retaining edges. This paper describes an efficient method to calculate the rank filter, which is a generalization of the median filter and includes it as a special case. The presented method is simpler than the method proposed previously by Danielsson. A strict proof is given for its validity. An application to the construction of a logical circuit realizing the algorithm is also described. [ABSTRACT FROM AUTHOR]