• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.8
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• pp.1275-1283
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• 1990

Perception of surfaces from range images plays a key role in 3-D object recognition. Recognition of 3-D objects from range images is performed by matching the perceived surface descriptions with stored object models. The first step of the 3-d object recognition from range images is image segmentation. In this paper, an approach for segmenting 3-D range images into symbolic surface descriptions using spatial Gabor filter is proposed. Since the phase of data has a lot of important information, the phase information with magnitude information can effectively segment the range imagery into regions satisfying a common homogeneity criterion. The phase and magnitude of Gabor filter can represent a unique featur vector at a point of range data. As a result, range images are trnasformed into feature vectors in 3-parameter representation. The methods not only to extract meaningful features but also to classify a patch information from range images is presented.

• Journal of Biomedical Engineering Research
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• v.41 no.5
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• pp.195-202
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• 2020

Needle detection in ultrasound images is sometimes difficult due to obstruction of fat tissues. Accurate needle detection using continuous ultrasound (CUS) images is a vital stage of treatment planning for tissue biopsy and brachytherapy. The main goal of the study is classified into two categories. First, new detection model, i.e. D-Attention Unet, is developed by combining the context information of 3D medical data and CUS images. Second, the D-Attention Unet model was compared with other models to verify its usefulness for needle detection in continuous ultrasound images. The continuous needle images taken with ultrasonic waves were converted into still images for dataset to evaluate the performance of the D-Attention Unet. The dataset was used for training and testing. Based on the results, the proposed D-Attention Unet model showed the better performance than other 3 models (Unet, D-Unet and Attention Unet), with Dice Similarity Coefficient (DSC), Recall and Precision at 71.9%, 70.6% and 73.7%, respectively. In conclusion, the D-Attention Unet model provides accurate needle detection for US-guided biopsy or brachytherapy, facilitating the clinical workflow. Especially, this kind of research is enthusiastically being performed on how to add image processing techniques to learning techniques. Thus, the proposed method is applied in this manner, it will be more effective technique than before.

• The Journal of the Korean dental association
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• v.56 no.10
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• pp.538-547
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• 2018

ITK-SNAP (http://www.itksnap.org) and 3D Slicer (CMFreg extension module; www.slicer.org) are open-source softwares which can be used for superimposition of cone-beam CT images. For superimposition, segmentation of bone is done with ITK-SNAP, and then voxel based superimposition of CBCT images can be performed using 3D Slicer. 3D Slicer has various visualization modules which are not provided in common commercial programs. 'Models' module is used to visualize two overlapping three-dimensional images, and this allows various visualizations by changing view mode and color of the model. In addition, differences between two CBCT images can be represented in a color map using 'ShapePopulationViewer' module. This report introduces how to superimpose and visualize CBCT images using ITK-SNAP and 3D Slicer, and the usefulness and limitations of both softwares will be discussed in comparison with commercial softwares.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1369-1375
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• 2016

In this paper, we present a depth extraction method of integral imaging using correlation between elemental images with phase only filter. Integral imaging is a passive three-dimensional (3D) imaging system records ray information of 3D objects through lenslet array by 2D image sensor, and displays 3D images by using the similar lenslet array. 2D images by lenslet array have different perspectives. These images are referred to as elemental images. Since the correlation can be calculated between elemental images, the depth information of 3D objects can be extracted. To obtain high correaltion between elemental images effectively, in this paper, we use phase only filter. Using this high correlation, the corresponding pixels between elemental images can be found so that depth information can be extracted by computational reconstruction technique. In this paper, to prove our method, we carry out optical experiment and calculate Peak Sidelobe Ratio (PSR) as a correlation metric.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.180-187
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• 2021

In this paper, we present a computational volumetric reconstruction method for three-dimensional (3D) photon counting imaging with enhanced visual quality when low-resolution elemental images are used under photon-starved conditions. In conventional photon counting imaging with low-resolution elemental images, it may be difficult to estimate the 3D scene correctly because of a lack of scene information. In addition, the reconstructed 3D images may be blurred because volumetric computational reconstruction has an averaging effect. In contrast, with our method, the pixels of the elemental image rearrangement technique and a Bayesian approach are used as the reconstruction and estimation methods, respectively. Therefore, our method can enhance the visual quality and estimation accuracy of the reconstructed 3D images because it does not have an averaging effect and uses prior information about the 3D scene. To validate our technique, we performed optical experiments and demonstrated the reconstruction results.

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.217-224
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• 2002

Many systems handle 3D-image were used. High-performance computer systems and techniques of compressing images to handle 3D-image were used. But there will be cost Problems, if GIS system is implemented, using the high-performance system. And if GIS system is implemented, using the techniques of compressing images, there will be some loss of a image. It will take a long processing time to handle 3D-images using a general PC because the size of 3D-image files are very huge. The parallel algorithm presented in the paper can improve speed to handle 3D-image using parallel computer system. The system uses the method of displacing images from nodes to screens, dividing a 3D-image into multiple sub images on multiple nodes. The performance of the presented algorithm showers improving speed by experiments.

• Journal of Digital Contents Society
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• v.12 no.2
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• pp.157-164
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• 2011

The purpose of this study was to examine the usefulness of 3D reconstruction images in breast MRI by performing a quantitative comparative analysis in patients diagnosed with DCIS. On a 3.0T MR scanner, subtraction images and 3D reconstruction images were obtained from 20 patients histologically diagnosed with ductal carcinoma in situ (DCIS). The findings from the quantitative image analysis are the following: The 3D reconstruction images showed higher SNR at the lesion area, ductal area, and fat area that of the subtraction image. In addition, the CNR were not significantly different in the lesion area itself between the subtraction images and 3D reconstruction images.

• Journal of radiological science and technology
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• v.42 no.6
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• pp.441-446
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• 2019

The purpose of this paper is to recognize the usefulness of the Phantom produced with 3D printing technology by reproducing the original phantom with 3D printing technology. Using CT, we obtained information from the original phantom. The acquired file was printed by the SLA method of ABS materials. For inspection, SPECT/CT was used to obtain images. We filled the both Phantom with a solution mixed with ^99mTcO4 1 mCi in 1 liter of water and acq uired images in accordance with the standard protocol. Using Image J, the SNR for each slice of the image was obtained. As a reference images, AC images were used. For the analysis of acquired images, ROI was set in the White mater and Gray mater sections of each image, and the average Intensity Value within the ROI were compared. According to the results of this study, 3D printed phantom's SNR is about 0.1 higher than the conventional phantom. And the ratio of Intensity Value was shown in the original 1 : 3.4, and the printed phantom was shown to be 1 : 3.2. Therefore, if Calibration Value is applied, It is assumed that it can be used as an alternative to the original.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.1-8
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• 2012

In this paper, we propose a rate-distortion optimization method to improve the coding efficiency of the conventional 3D-DCT based compression method using adaptive block mode selection for integral images. In the conventional 3D-DCT based compression method, 3D-DCT blocks of variable block sizes are adaptively selected depending on the characteristics of integral images, and then 3D-DCT is performed. The proposed method applies a rate-distortion optimization to determine the optimal block mode. In addition, we suggest the optimal Lagrangian parameter for integral images. Experimental results show that the proposed method gives bit-rate reduction of about 5%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.68-75
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• 2006

In this paper, we propose an adaptive video watermarking method using human visual system(HVS) and characteristics of three-dimensional cosine transform (3D-DCT) cubes. We classify 3D-DCT cubes into three patterns according to the distribution of coefficients in the 3D-DCT cube: cube with motion and textures, cube with high textures and little motion, and cube with little textures and line motion. Images are also classified into three types according to the ratio of these patterns: images with motion and textures, images with high textures and little motion, and images with little textures and little motion. The proposed watermarking method adaptivelyinserts the watermark on the coefficients of the mid-range in the 3D-DCT cube using the appropriately learned sensitivity table and the proportional constants depending on the patterns of 3D-DCT cubes and types of images. Experimental results show that the proposed method achieves better performance in terms of invisibility and robustness than the previous method.