• Journal of Chest Surgery
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• v.38 no.8 s.253
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• pp.583-588
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• 2005

Congenital tracheal stenosis can be a life-threatening disease, especially in cases involving the long-segment of the trachea. When patients are symptomatic immediately after birth or develop an accompanying complex cardiac anomaly, surgical repair can be a considerable challenge. We experienced a tracheoplasty in one early infant weighing 2.6 kg and one neonate who had ventilator dependency from long-segment congenital tracheal stenosis and congenital cardiac anomaly. One early infant, who had diffuse stenosis of distal trachea after ventricular septal defect closure, underwent resection and extended end to end anastomosis. One neonate who had diffuse stenosis of proximal trachea with tetralogy of Fallot (TOF), underwent slide tracheoplasty with total correction for TOF Postoperative chest computed tomography showed widely patent trachea. Both infants are now well without symptoms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.

• Journal of the korean academy of Pediatric Dentistry
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• v.27 no.3
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• pp.388-393
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• 2000

Cleft lip and palate is one of the most common congenital defects in oro-maxillo-facial region. Because most patients undergo surgical repair in early life, the sagittal jaw relationships used to be deteriorated gradually from palate surgery up to adulthood. Also, the maxillary lateral incisor may be absent or atypical-shaped in the cleft site and may not erupt or erupt ectopically, so multidisciplinary dental cares are needed for cleft lip and palate patients. The effects of the cleft lip and alveolus seem to be limited to that part of the dentofacial complex that surrounds the cleft area. In the maxillary arch, the anterior part of the non cleft segment has a tendency to be rotated forward. On the other hand, the cleft segment has a tendency to rotated slightly medially ; hence, the tendency for canines to be edge-to-edge and sometimes in crossbite. Lip and alveolus surgery adequetely correct these problems, with little untoward effect on the skeletal maxillary-mandible relationships. In this report, the patient has a repaired lip and cleft alveolus on the left side with congenital missing on '62, '22, oronasal fistula, and skeletal class III malocclusion which is not affected by lip surgery. Dental treatments for this patient including orthodontic(space supervision, functional regulator in mixed dentition, fixed therapy in permanent dentition) and prosthodontic(removable obturator with key and keyway attachment and Konus crown) therapy were performed to improve the patient's functions and esthetics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.675-686
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• 2005

In this paper, we propose an efficient face region detection technique for the content-based video summarization. To segment video, shot changes are detected from a video sequence and key frames are selected from the shots. We select one frame that has the least difference between neighboring frames in each shot. The proposed face detection algorithm detects face region from selected key frames. And then, we provide user with summarized frames included face region that has an important meaning in dramas or movies. Using Bayes classification rule and statistical characteristic of the skin pixels, face regions are detected in the frames. After skin detection, we adopt the projection method to segment an image(frame) into face region and non-face region. The segmented regions are candidates of the face object and they include many false detected regions. So, we design a classifier to minimize false lesion using CART. From SGLD matrices, we extract the textual feature values such as Inertial, Inverse Difference, and Correlation. As a result of our experiment, proposed face detection algorithm shows a good performance for the key frames with a complex and variant background. And our system provides key frames included the face region for user as video summarized information.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.7
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• pp.53-61
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• 2008

Consider a typical wireless sensor network in which stem nodes form the backbone network of mesh topology while each stem node together with leaf nodes in its vicinity forms a subnetwork of star topology. In such a wireless sensor network, we must heed the following when we design a MAC scheme supporting the packet delivery from a leaf node to a stem node. First, leaf nodes are usually battery-powered and it is difficult to change or recharge their batteries. Secondly, a wireless sensor network is often deployed to collect and update data periodically. Late delivery of a data segment by a sensor node causes the sink node to defer data processing and the data segment itself to be obsolete. Thirdly, extensive signaling is extremely limited and complex computation is hardly supported. Taking account of these facts, a MAC scheme must be able to save energy and support timeliness in packet delivery while being simple and robust as well. In this paper, we propose a version of ALOHA as a MAC scheme for a wireless sensor network. While conserving the simplicity and robustness of the original version of ALOHA, the proposed version of ALOHA possesses a distinctive feature that a sensor node decides between stop and continuation prior to each delivery attempt for a packet. Such a decision needs a stopping rule and we suggest a Bayes stopping rule. Note that a Bayes stopping rule minimizes the Bayes risk which reflects the energy, timeliness and throughput losses. Also, a Bayes stopping rule is practical since a sensor node makes a decision only using its own history of delivery attempt results and the prior information about the failure in delivery attempt. Numerical examples confirm that the proposed version of ALOHA employing a Bayes stopping rule is a useful MAC scheme in the severe environment of wireless sensor network.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.592-601
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• 2019

For coronary procedures, X-ray angiogram images are useful for diagnosing and assisting procedures. It is challenging to accurately segment a coronary artery using only a single segmentation model in 2D X-ray images due to a complex structure of three-dimensional coronary artery, especially from phenomenon of vessels being broken in the middle or end of coronary artery. In order to solve these problems, the initial segmentation is performed using an existing single model, and the candidate regions for the sophisticate correction is estimated based on the initial segment, and the local patch-based correction is performed in the candidate regions. Through this research, not only the broken coronary arteries are re-connected, but also the distal part of coronary artery that is very thin is additionally correctly found. Further, the performance can be much improved by combining the proposed correction method with any existing coronary artery segmentation method. In this paper, the U-net, a fully convolutional network was chosen as a segmentation method and the proposed correction method was combined with U-net to demonstrate a significant improvement in performance through X-ray images from several patients.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.323-330
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• 2023

The development of an analysis model that reflects the microstructure characteristics of polyvinyl alcohol (PVA) fiber-reinforced cementitious composites, which have a highly complex microstructure, enables synergy between efficient material design and real experiments. PVA fiber orientations are an important factor that influences the mechanical behavior of PVA fiber-reinforced cementitious composites. Owing to the difficulty in distinguishing the gray level value obtained from micro-CT images of PVA fibers from adjacent phases, fiber segmentation is time-consuming work. In this study, a micro-CT test with a voxel size of 0.65 ㎛³ was performed to investigate the three-dimensional distribution of fibers. To segment the fibers and generate training data, histogram, morphology, and gradient-based phase-segmentation methods were used. A U-net model was proposed to segment fibers from micro-CT images of PVA fiber-reinforced cementitious composites. Data augmentation was applied to increase the accuracy of the training, using a total of 1024 images as training data. The performance of the model was evaluated using accuracy, precision, recall, and F1 score. The trained model achieved a high fiber segmentation performance and efficiency, and the approach can be applied to other specimens as well.

• International Journal of Contents
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• v.10 no.4
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• pp.1-10
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• 2014

In this paper, we propose a method to build an accurate initial trimap for the GrabCut algorithm without the need for human interaction. First, we identify a rough candidate for the label region of a bottle by applying a saliency map to find a salient area from the image. Then, the Hough Transformation method is used to detect the left and right borders of the label region, and the k-means algorithm is used to localize the upper and lower borders of the label of the bottle. These four borders are used to build an initial trimap for the GrabCut method. Finally, GrabCut segments accurate regions for the label. The experimental results for 130 wine bottle images demonstrated that the saliency map extracted a rough label region with an accuracy of 97.69% while also removing the complex background. The Hough transform and projection method accurately drew the outline of the label from the saliency area, and then the outline was used to build an initial trimap for GrabCut. Finally, the GrabCut algorithm successfully segmented the bottle label with an average accuracy of 92.31%. Therefore, we believe that our method is suitable for product label recognition systems that automatically segment product labels. Although our method achieved encouraging results, it has some limitations in that unreliable results are produced under conditions with varying illumination and reflections. Therefore, we are in the process of developing preprocessing algorithms to improve the proposed method to take into account variations in illumination and reflections.

• BMB Reports
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• v.34 no.2
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• pp.109-113
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• 2001

The Serratia marcescens metalloprotease inhibitor (SmaPI) is a proteinase inhibitor toward Serratia marcescens metalloprotease (SMP). The three-dimensional structure of SmaPI was calculated by computer modeling using the structure complex between SMP and the Erwinia chrysanthemi inhibitor as a template. Based on this model structure, the substitution of the amino acid residues, Ala4, Leu-5, Pro-6, and Thr-7, were located at the hinge region of the N-terminal segment by site-directed mutagenesis. Although the A4R and T7A mutant SmaPIs showed a nearly full inhibitory activity, the inhibitory activity of SmaPI decreased significantly when the Leu-5 was converted to Ala, Gly, Ile, or Val. Surprisingly, the L5I and L5V mutant SmaPIs showed less inhibitory activities than the L5A mutant. From these results, we suggested that the orientations and positions of respective aliphatic groups in the side-chain of position 5 mainly affected the inhibitory activity of SmaPI. The overall side-chain hydrophobicity was only slightly affected. The side-chain of the Leu-5 residue contributed approximately 0.79 kcal/mol out of 8.44 kcal/mol to the binding of SmaPI with SMP The inhibitory activities of P6A and F6G were also severely decreased. The Pro-6 may have a critical role in maintaining the strict conformation of the N-terminal portion that may be important in the inhibitory activity of SmaPI. In conclusion, Leu-5 and Pro-6 have crucial roles in the inhibitory function of SmaPI toward SMP.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.8
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• pp.407-415
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• 2008

This paper presents novel segmentation and transition techniques for dancing motion synthesis. The segmentation method for dancing motions is based on Laban Movement Analysis (LMA). We assume a dance sequence as a set of small dancing motions. To segment a dancing motion is a subjective, psychological, and complex problem, so we extract the shape factor of LMA from a dance motion and observe shape's changes to find the boundaries of dance segments. We also introduce a transition method that meets constraints on the feet. This method that is based on a linear interpolation modifies the intermediate posture motion after analyzing footprint positions. The posture could be a key-frame between source motion and target motion on the transition. With the proposed techniques, it would be easy for multimedia applications to generate plausible dance motions.