• Title/Summary/Keyword: Segmentation model

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Comparison of Performance of Medical Image Semantic Segmentation Model in ATLASV2.0 Data (ATLAS V2.0 데이터에서 의료영상 분할 모델 성능 비교)

  • So Yeon Woo;Yeong Hyeon Gu;Seong Joon Yoo
    • Journal of Broadcast Engineering
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    • v.28 no.3
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    • pp.267-274
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    • 2023
  • There is a problem that the size of the dataset is insufficient due to the limitation of the collection of the medical image public data, so there is a possibility that the existing studies are overfitted to the public dataset. In this paper, we compare the performance of eight (Unet, X-Net, HarDNet, SegNet, PSPNet, SwinUnet, 3D-ResU-Net, UNETR) medical image semantic segmentation models to revalidate the superiority of existing models. Anatomical Tracings of Lesions After Stroke (ATLAS) V1.2, a public dataset for stroke diagnosis, is used to compare the performance of the models and the performance of the models in ATLAS V2.0. Experimental results show that most models have similar performance in V1.2 and V2.0, but X-net and 3D-ResU-Net have higher performance in V1.2 datasets. These results can be interpreted that the models may be overfitted to V1.2.

Prerequisite Research for the Development of an End-to-End System for Automatic Tooth Segmentation: A Deep Learning-Based Reference Point Setting Algorithm (자동 치아 분할용 종단 간 시스템 개발을 위한 선결 연구: 딥러닝 기반 기준점 설정 알고리즘)

  • Kyungdeok Seo;Sena Lee;Yongkyu Jin;Sejung Yang
    • Journal of Biomedical Engineering Research
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    • v.44 no.5
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    • pp.346-353
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    • 2023
  • In this paper, we propose an innovative approach that leverages deep learning to find optimal reference points for achieving precise tooth segmentation in three-dimensional tooth point cloud data. A dataset consisting of 350 aligned maxillary and mandibular cloud data was used as input, and both end coordinates of individual teeth were used as correct answers. A two-dimensional image was created by projecting the rendered point cloud data along the Z-axis, where an image of individual teeth was created using an object detection algorithm. The proposed algorithm is designed by adding various modules to the Unet model that allow effective learning of a narrow range, and detects both end points of the tooth using the generated tooth image. In the evaluation using DSC, Euclid distance, and MAE as indicators, we achieved superior performance compared to other Unet-based models. In future research, we will develop an algorithm to find the reference point of the point cloud by back-projecting the reference point detected in the image in three dimensions, and based on this, we will develop an algorithm to divide the teeth individually in the point cloud through image processing techniques.

Motion-Field Segmentation for Video Coding (동영상 부호화를 위한 움직임 필터 영역화)

  • 강동욱;이승준;이충웅
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.7
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    • pp.141-148
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    • 1994
  • This paper presents a new method for reducing the blocking artifacts there by increasing the prediction gains of the block-based motion compensation keeping the amount of the motion information to be transmitted intact. The new method improves the motion compensation along the edges of moving objects by segmenting the motion field at the pixel resolution based on the model that the motion compensated image is the maximum a poseriori estimate of the current frame.

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Text-dependent Speaker Verification System Over Telephone Lines (전화망을 위한 어구 종속 화자 확인 시스템)

  • 김유진;정재호
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.663-667
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    • 1999
  • In this paper, we review the conventional speaker verification algorithm and present the text-dependent speaker verification system for application over telephone lines and its result of experiments. We apply blind-segmentation algorithm which segments speech into sub-word unit without linguistic information to the speaker verification system for training speaker model effectively with limited enrollment data. And the World-mode] that is created from PBW DB for score normalization is used. The experiments are presented in implemented system using database, which were constructed to simulate field test, and are shown 3.3% EER.

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체계적인 웹사이트 개발 Framework

  • 강인태;박용태
    • Proceedings of the Technology Innovation Conference
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    • 2000.06a
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    • pp.105-120
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    • 2000
  • Rapid spread of Internet, there appear so many commercial wedsites. Websites are not only tools to advertise a company or a product, but also value-added products inself. So we need a systematic approach(planning, design, implementation) to develop a website. But existing reserches on website development have corvered only technological issues such as network and HCI(Human Computer Intercation). In this research a framework is proposed to develop a website systematically using database of existing websites. This framework is composed of several stages-target customer segmentation, determination of services on website, dtermination of business model, functinal positioning, and evaution.

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Research about auto-segmentation via SVM (SVM을 이용한 자동 음소분할에 관한 연구)

  • 권호민;한학용;김창근;허강인
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2220-2223
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    • 2003
  • In this paper we used Support Vector Machines(SVMs) recently proposed as the loaming method, one of Artificial Neural Network, to divide continuous speech into phonemes, an initial, medial, and final sound, and then, performed continuous speech recognition from it. Decision boundary of phoneme is determined by algorithm with maximum frequency in a short interval. Recognition process is performed by Continuous Hidden Markov Model(CHMM), and we compared it with another phoneme divided by eye-measurement. From experiment we confirmed that the method, SVMs, we proposed is more effective in an initial sound than Gaussian Mixture Models(GMMs).

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MR, CT 영상을 활용한 인체 부위에 따른 최적의 영상 분할 알고리듬 연구

  • 호동수;이형구;김성현;김도일;서태석;최보영;이진희
    • Proceedings of the KSMRM Conference
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    • 2003.10a
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    • pp.78-78
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    • 2003
  • 목적: 이전에는 손쉽게 구할 수 있는 표준데이터를 가지고 visual human body model을 형성하였다. 주로 팬텀이나, 외국인의 데이터를 가지고 만든 것이기 때문에 우리가 실제 실험에 쓰려면 큰 차이가 있었다. 그래서 본 연구에서는 실제 우리나라 사람 중 동일 인물의 MR와 CT 이미지를 가지고 인체 모델을 만들고자 하였다. 그러기 위해서 먼저 인체의 MR, CT영상에 대한 특징을 분석해야 했고, 이것을 바탕으로 영상 분할(Image Segmentation)을 하였다. 인체 부위에 따라 영상 분할 방법도 그 차이가 있음을 알 수 있었다.

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An Edge-Based Algorithm for Discontinuity Adaptive Image Smoothing (에지기반의 불연속 경계적응 영상 평활화 알고리즘)

  • 강동중;권인소
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.273-273
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    • 2000
  • We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.

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