Jaeyoun Yi

A deblocking filter with two separate modes in block-based video coding

This paper presents a method to remove blocking artifacts in low bit-rate block-based video coding. The proposed algorithm has two separate filtering modes, which are selected by pixel behavior around the block boundary. In each mode, proper one-dimensional filtering operations are performed across the block boundary along the horizontal and vertical directions, respectively. In the first mode, corresponding to flat regions, a strong filter is applied inside the block as well as on the block boundary because the flat regions are more sensitive to the human visual system (HVS) and the artifacts propagated from the previous frame due to motion compensation are distributed inside the block. In the second mode, corresponding to other regions, a sophisticated smoothing filter which is based on the frequency information around block boundaries, is used to reduce blocking artifacts adaptively without introducing undesired blur. Even though the proposed deblocking filter is quite simple, it improves both subjective and objective image quality for various image features.

A locally adaptive region growing algorithm for vascular segmentation

To segment vascular structures in 3‐D CTA/MRA images, this article presents a new region growing algorithm based on local cube tracking. In the proposed algorithm, a small local cube is segmented to detect a vessel segment, and the following local cube(s) is determined based on the segmentation result. This procedure is repeated until the segmentation is completed. By confining the segmentation inside each local cube, a robust result can be obtained even in a tubular structure of steadily changing intensity. For segmentation, a locally adaptive and competitive region growing scheme is adopted to obtain well‐defined vessel boundaries. It should be emphasized that the proposed algorithm can detect all branches with practically acceptable computational complexity. In addition, its segmentation result is represented as a tree structure having many branches so that a user may easily correct the result branch‐by‐branch, if necessary. Experimental results from real images prove that the proposed algorithm produces prospective vessel segmentation results for 3‐D CTA/MRA images and segments vessels of various sizes well, including stenoses and aneurysms.

Visually guided spine biopsy simulator with force feedback

A new surgical simulator is developed for spine needle biopsy, that provides realistic visual and force feedback to a trainee in the PC environment. This system is composed of four parts: a 3D human model, visual feedback tool, force feedback device, and an evaluation section. The 3D human model includes multi-slice XCT images, segmentation results, and force-feedback parameters. A block-based technique is adopted for efficient handling of large amounts of data and for easy control of rendering parameters such as opacity. For visual feedback, we implement a virtual CT console box and a 3D visualization tool providing MIP, MPR, summed voxel projection, and realistic 3D color volume rendering view. The visualization tool is for interactive 3D path planning. A haptic device is used to provide force feedback to the biopsy needle during simulation. The interactive force is generated in a voxel-based manner. After each simulation, the evaluation section provides a performance analysis to the trainee. We implemented the system by attaching a 3DOF PHANToMTM device to a PC with 600MHz Pentium III Dual CPUs and 512Mbyte RAM.

Vascular segmentation algorithm using locally adaptive region growing based on centerline estimation

In this paper, we propose a new region-based approach on the basis of centerline estimation, to segment vascular networks in 3D CTA/MRA images. The proposed algorithm is applied repeatedly to newly updated local cubes. It consists of three tasks; local region growing, surfacic connected component labeling, and next local cube detection. The cube size is adaptively determined according to the estimated diameter. After region growing inside a local cube, we perform the connected component labeling procedure on all 6 faces of the current local cube (surfacic component labeling). Then the detected surfacic components are put into a queue to serve as seeds of following local cubes. Contrary to conventional centerline-tracking methods, the proposed algorithm can detect all bifurcations without any restriction because a region-based method is used at every local cube. And by confining region growing to a local cube, it can be more effective in producing prospective results. It should be noticed that the segmentation result is divided into several branches, so a user can easily edit the result branch-by-branch. The proposed method can automatically generate a flyway in a virtual angioscopic system since it provides a tree structure of the detected branches.

Automatic flight path generation in a virtual colonoscopy system

Virtual colonoscopy is a computerized procedure to examine colonic polyps from a CT data set. To automatically fly through a long and complex-shaped colon with a virtual camera, we propose an efficient method to simultaneously generate view-positions and view-directions. After obtaining a 3-D binary colon model, we find an initial path that represents rough camera directions and positions along it. Then, by using this initial path, we generate control planes to find a set of discrete view-positions, and view planes to obtain the corresponding view-directions, respectively. Finally, for continuous and smooth navigation, the obtained view-positions and directions are interpolated using the B-spline method. Here, by imposing a constraint to control planes, penetration and collision can be avoided in the interpolated result. Effectiveness of the proposed algorithm is examined via computer simulations using the several phantoms to simulate the characteristics of human colon, namely, high-curvatures and complex structure. Simulation results show that the algorithm provides the view-positions and view-directions suitable for covering more 3-D surface area in the navigation. Also, prospective results are obtained for human colon data with a high processing speed of less than 1 minute with a 2 GHz standard PC.

Efficient segmentation algorithm for 3D medical image data using a region-growing-based tracking technique

In this paper, we propose an efficient semi-automatic algorithm to segment a 3-D object by using a given segmentation result in a single slice. In the proposed algorithm, the segmentation is performed slice-by-slice using z correlation as well as xy correlation based on the assumption that the region to be segmented is homogeneous and has discernable boundaries. We first estimate a parametric motion model of the organ from the previous slice to the current slice, and find an estimated boundary of the organ by projecting the previous result. Then, we extract 3 kinds of seeds in the current slice by using the projected boundaries and the pixel luminance values. All extracted seeds are grown to produce the precise boundary of the organ. And wrong boundary portions due to region growing at low gradient areas are corrected by the post-processing based on a Fourier descriptor. Finally, to catch up on newly appearing areas, a two-way tracking method is applied. The proposed algorithm provides satisfactory results in segmenting kidneys from an X- ray CT body image set of 82 slices.

Deblocking filter with two separate modes in block-based video coding

This paper presents a method to remove blocking artifacts in low bit-rate block-based video coding. The proposed algorithm has two separate filtering modes, which are selected by pixel behavior around the block boundary. In each mode, proper 1D filtering operations are performed across the block boundary along horizontal and vertical directions, respectively. In the first mode corresponding flat regions, a strong filter is applied inside the block as well as on the block boundary, because the flat regions are more sensitive to the human vidual system and the artifacts propagated from the previous frame due to motion compensation are distributed inside the block. In the second mode corresponding to other regions, a sophisticated smoothing filter, which is based on the frequency information around block boundaries, is used to reduce blocking artifacts adaptively without introducing undesired blur. Even though the proposed deblocking filter is quite simple, it improves both subjective and objective image quality for various image features.

Automatic depth determination for sculpting based on volume rendering

An interactive sculpting tool is being widely used to segment a 3-D object on a volume rendered image for improving the intuitiveness. However, it is very hard to segment only an outer part of a 3-D object, since the conventional method cannot handle the depth of removal. In this paper, we present an effective method to determine the depth of removal, by using the proposed spring-rod model and the voxel-opacity. To determine the depth of removal, the 2-D array of rigid rods is constructed after a 2-D closed loop is defined on a volume-rendered image by a user. Each rigid rod is located at a digitized position inside the user-drawn closed loop and its direction is coincident with that of projecting rays. And every rod has a frictionless ball, which is interconnected with its neighboring balls through ideal springs. In addition, we assume that an external force defined by the corresponding voxel-opacity value is exerted on each ball along the direction of the projected ray. Using this spring-rod system model, we can determine final positions of balls, which represent the depths of removal. Then, the outer part can be properly removed. The proposed method is applied to various medical image data and is evaluated to provide robust results with easy user-interaction.

Semantic object segmentation scheme for x-ray body images

In the segmentation process based on a watershed algorithm, a proper seed extraction is very important for segmentation quality because improper seeds can produce undesirable results such as over-segmentation or under-segmentation. Especially, an appropriate seed-extraction algorithm is indispensable in segmenting XCT body images where many organs, except lungs and bones, are in very narrow gray-level ranges with very low contrasts. In the proposed scheme, we divide an image into 4 sub-images by windowing its gray-level histogram, and extract proper seeds from each sub-image by different method according to its characteristic. Then, by using all the seeds obtained from the four separated sub-images, we perform the watershed algorithm to complete the image segmentation. The proposed segmentation method has been successfully applied to X-ray CT body images.