• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1997년도 춘계학술대회
• /
• pp.465-468
• /
• 1997

A Study on Computer Assisted Diagnosis (CAD) system extract ing lung cancer part from Digital X-ray Computerized Tomography(CT) image is discussed in this paper. It is very crucial to segment the image of lung into the three organ area such as inside, outside and the hilum so that the variant image processing algorithm can be applied an each area respectively. In this paper, the efficient algorithm extracting lung cancer part is proposed with characterizing lung hilum part and its associated vessel patterns.

• Archives of Plastic Surgery
• /
• 제39권4호
• /
• pp.309-316
• /
• 2012

Computer aided design and manufacturing (CAD/CAM) technology today is the standard in manufacturing industry. The application of the CAD/CAM technology, together with the emerging 3D medical images based virtual surgical planning (VSP) technology, to craniomaxillofacial reconstruction has been gaining increasing attention to reconstructive surgeons. This article illustrates the components, system and clinical management of the VSP and CAD/CAM technology including: data acquisition, virtual surgical and treatment planning, individual implant design and fabrication, and outcome assessment. It focuses primarily on the technical aspects of the VSP and CAD/CAM system to improve the predictability of the planning and outcome.

• 치과방사선
• /
• 제29권2호
• /
• pp.387-396
• /
• 1999

In dentistry. RadioVisioGraphy was introduced as a first electronic dental x-ray imaging modality in 1989. Thereafter. many types of direct digital radiographic system have been produced in the last decade. They are based either on charge-coupled device(CCD) or on storage phosphor technology. In addition. new types of digital radiographic system using amorphous selenium. image intensifier etc. are under development. Advantages of digital radiographic system are elimination of chemical processing, reduction in radiation dose. image processing, computer storage. electronic transfer of images and so on. Image processing includes image enhancement. image reconstruction. digital subtraction, etc. Especially digital subtraction and reconstruction can be applied in many aspects of clinical practice and research. Electronic transfer of images enables filmless dental hospital and teleradiology/teledentistry system. Since the first image management and communications system(IMACS) for dentomaxillofacial radiology was reported in 1992. IMACS in dental hospital has been increasing. Meanwhile. researches about computer-assisted diagnosis, such as structural analysis of bone trabecular patterns of mandible. feature extraction, automated identification of normal landmarks on cephalometric radiograph and automated image analysis for caries or periodontitis. have been performed actively in the last decade. Further developments in digital radiographic imaging modalities. image transmission system. imaging processing and automated analysis software will change the traditional clinical dental practice in the 21st century.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권4호
• /
• pp.1146-1165
• /
• 2022

A huge amount of data in the form of videos and images is being produced owning to advancements in sensor technology. Use of low performance commodity hardware coupled with resource heavy image processing and analyzing approaches to infer and extract actionable insights from this data poses a bottleneck for timely decision making. Current approach of GPU assisted and cloud-based architecture video analysis techniques give significant performance gain, but its usage is constrained by financial considerations and extremely complex architecture level details. In this paper we propose a data pipeline system that uses open-source tools such as Apache Spark, Kafka and OpenCV running over commodity hardware for video stream processing and image processing in a distributed environment. Experimental results show that our proposed approach eliminates the need of GPU based hardware and cloud computing infrastructure to achieve efficient video steam processing for face detection with increased throughput, scalability and better performance.

• 한국정보과학회논문지:시스템및이론
• /
• 제33권11호
• /
• pp.853-858
• /
• 2006

본 논문에서는 깊이 영상기반의 3차원 그래픽 객체에 대하여 그래픽 처리 장치(Graphics Processing Unit, GPU)의 가속을 이용한 고속의 렌더링 기법을 제안한다. 제안하는 알고리즘은 최근의 그래픽 처리 장치의 새로운 특징과 프로그래밍이 가능한 쉐이더 기법을 이용하여, 속도가 느리거나 정적인 조명과 같은 기존의 일반적인 깊이 영상기반 렌더링 방법이 갖고 있는 단점을 극복할 수 있다. 깊이 영상기반 데이타의 3차원 변환 및 조명에 의한 효과 연산은 정점 쉐이더(vertex shader)에서 수행을 하고, 점 데이타의 적응적인 스플래팅(splatting)은 화소 쉐이더(fragment shader)에서 수행된다. 모의 실험결과, 소프트웨어 렌더링 또는 OpenGL 기반의 렌더링과 비교해서 괄목할 만한 렌더링 속도의 향상이 이루어졌다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제5권9호
• /
• pp.1613-1631
• /
• 2011

Several metrics have been reported in the literature to assess stereo image quality, mostly based on visual attention or human visual sensitivity based distortion prediction with the help of disparity information, which do not consider the combined aspects of human visual processing. In this paper, visual attention and depth assisted stereo image quality assessment model (VAD-SIQAM) is devised that consists of three main components, i.e., stereo attention predictor (SAP), depth variation (DV), and stereo distortion predictor (SDP). Visual attention is modeled based on entropy and inverse contrast to detect regions or objects of interest/attention. Depth variation is fused into the attention probability to account for the amount of changed depth in distorted stereo images. Finally, the stereo distortion predictor is designed by integrating distortion probability, which is based on low-level human visual system (HVS), responses into actual attention probabilities. The results show that regions of attention are detected among the visually significant distortions in the stereo image pair. Drawbacks of human visual sensitivity based picture quality metrics are alleviated by integrating visual attention and depth information. We also show that positive correlation with ground-truth attention and depth maps are increased by up to 0.949 and 0.936 in terms of the Pearson and the Spearman correlation coefficients, respectively.

• Journal of Computing Science and Engineering
• /
• 제8권2호
• /
• pp.119-128
• /
• 2014

The appearance of retinal blood vessels is an important diagnostic indicator of serious disease, such as hypertension, diabetes, cardiovascular disease, and stroke. Automatic segmentation of the retinal vasculature is a primary step towards automatic assessment of the retinal blood vessel features. This paper presents an automated method for the enhancement and segmentation of blood vessels in fundus images. To decrease the influence of the optic disk, and emphasize the vessels for each retinal image, a multidirectional morphological top-hat transform with rotating structuring elements is first applied to the background homogenized retinal image. Then, an improved multiscale line detector is presented to produce a vessel response image, and yield the retinal blood vessel tree for each retinal image. Since different line detectors at varying scales have different line responses in the multiscale detector, the line detectors with longer length produce more vessel responses than the ones with shorter length; the improved multiscale detector combines all the responses at different scales by setting different weights for each scale. The methodology is evaluated on two publicly available databases, DRIVE and STARE. Experimental results demonstrate an excellent performance that approximates the average accuracy of a human observer. Moreover, the method is simple, fast, and robust to noise, so it is suitable for being integrated into a computer-assisted diagnostic system for ophthalmic disorders.

• 한국컴퓨터그래픽스학회논문지
• /
• 제8권2호
• /
• pp.15-22
• /
• 2002

영상분할이란 영상내의 이미지 상의 특정한 의미가 있는 영역으로 나누는 영상처리 방법을 일컫는다. 이미지 합성이나 분석을 위해서는 구분된 영역이 최대한 인간이 의미를 부여할 수 있는 물체를 나타내는 것이 바람직하나, 현재의 컴퓨터에의한 자동 영상이해 기법으로는 그 학문적 및 기술적인 한계로 인하여 영역의 분할이 수치적인 의미 이상을 가지게하기 어렵다. 따라서, 사용자가 결정적인 물체 경계의 정보를 제공하고 그에 기반하여 처리하는 HCI(Human Computer Interaction)개념을 도입하면 효과적인 결과를 얻을 수 있다. 기존의 "지능형 가위" (Intelligent Scissors)나 스네이크 (Snake) 방법 등에서도 사용자의 입력이 결과에 결정적인 역할을 하는 것을 보여준다 [1][2]. 본 논문은 기존의 방법에 비하여 미세한 영역의 경계를 추출 및 추적을 향상할 수 있는 효율적인 대화형 영상분할 기법을 제안한다. 제시된 방법은 지능형 가위의 개념에 일부 기반하나 안정된 경계선 추출을 위하여 이미 영상처리분야에서 확립된 캐니 경계 검출법(Canny Edge Detector)을 사용한다. 그리고 캐니 경계 검출법으로 잘 탐지되지 않는 경계선 부분에 대한 검출을 위하여 경계 "재봉법"(Sewing Method)을 제시하였으며, 작업 효과와 효율을 증진 시키기 위하여 인접 화소들을 검색하는 순서와 검색 대상 화소를 지정하는 5-방향 경계 추적 방법(5-Direction Edge-Following Method)을 제안하였다.

• 대한토목학회논문집
• /
• 제13권5호
• /
• pp.191-199
• /
• 1993

스캐닝된 지상사진의 수치화상데이타를 이용하여 정사투영화상을 작성하는 기법을 제시하였다. 수치화상데이타를 얻기 위하여 촬영된 지상사진을 CCD 카메라 스캐너로 스캐닝한 후, 4차 다항식을 적용하여 스캐닝과정에서 생긴 기하왜곡을 보정하였다. 좌우 화상에 있어서 각 화소의 동일점을 찾기 위하여 자동매칭기법을 적용하였으며 외부표정요소를 이용한 공간교차이론으로 각 화소의 3차원 지상좌표를 구하였다. 얻어진 3차원 지상좌표와 우측화상데이타값으로부터, 거리의 역에 따른 가중평균법을 사용하여 1개 화소의 크기가 $1mm{\times}1mm$ 되는 정사투영화상을 작성하였다. 검사점에 대하여, 작성된 정사투영화상상의 X 및 Y좌표와 지상관측된 좌표를 비교하여 정사투영화상 작성기법의 유효성을 검증할 수 있었다.

• Imaging Science in Dentistry
• /
• 제52권4호
• /
• pp.383-391
• /
• 2022

Purpose: Periodontitis, the most prevalent chronic inflammatory condition affecting teeth-supporting tissues, is diagnosed and classified through clinical and radiographic examinations. The staging of periodontitis using panoramic radiographs provides information for designing computer-assisted diagnostic systems. Performing image segmentation in periodontitis is required for image processing in diagnostic applications. This study evaluated image segmentation for periodontitis staging based on deep learning approaches. Materials and Methods: Multi-Label U-Net and Mask R-CNN models were compared for image segmentation to detect periodontitis using 100 digital panoramic radiographs. Normal conditions and 4 stages of periodontitis were annotated on these panoramic radiographs. A total of 1100 original and augmented images were then randomly divided into a training (75%) dataset to produce segmentation models and a testing (25%) dataset to determine the evaluation metrics of the segmentation models. Results: The performance of the segmentation models against the radiographic diagnosis of periodontitis conducted by a dentist was described by evaluation metrics(i.e., dice coefficient and intersection-over-union [IoU] score). MultiLabel U-Net achieved a dice coefficient of 0.96 and an IoU score of 0.97. Meanwhile, Mask R-CNN attained a dice coefficient of 0.87 and an IoU score of 0.74. U-Net showed the characteristic of semantic segmentation, and Mask R-CNN performed instance segmentation with accuracy, precision, recall, and F1-score values of 95%, 85.6%, 88.2%, and 86.6%, respectively. Conclusion: Multi-Label U-Net produced superior image segmentation to that of Mask R-CNN. The authors recommend integrating it with other techniques to develop hybrid models for automatic periodontitis detection.