• Title/Summary/Keyword: Medical Image Segmentation

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Three-dimensional Boundary Segmentation using Multiresolution Deformable Model (다해상도 변형 모델을 이용한 3차원 경계분할)

  • 박주영;김명희
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04b
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    • pp.592-594
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    • 2000
  • 변형모델(deformable model)은 볼륨의료영상(volumetric medical image)으로부터 복잡한 인체기관의 3차원적 경계를 분할해내기 위해 효과적인 방법을 제공한다. 그러나, 기존 변형모델은 초기와 의존성, 오목한 경계(concavity) 분할의 비적합성, 그리고 모델내 요소간 자체교차(self-intersection)의 제한점을 가지고 있었다. 본 연구에서는 이러한 제한점을 극복하고, 오목한 구조를 포함하는 복잡한 인체기관의 경계를 분할하기에 적합한 새로운 변형모델을 제안하였다. 제안한 변형모델은 볼륨영상 피라미드(pyramid)를 기반으로 다해상도(multiresolution)의 모델 정제화(refinement)를 수행한다. 다해상도 모델 정제화는 전역적 시셈플링(global resampling) 및 지역적 리샘플링(local resampling)를 통하여 저해상도의 모델로부터 점차 고해상도의 모델로 이동하면서 객체의 경계를 계층적으로 분할해가는 방법이다. 다해상도 모델에 의한 계층적 경계 분할은 초기화 조건에의 의존성을 극복할 수 있게할 뿐 아니라, 빠른 속도로 원하는 객체의 경계에 수렴할 수 있게 한다. 또한 지역적 리샘플링은 모델 구성요소의 정규화를 수행함으로써 객체의 오목한 부분을 성공적으로 분할할 수 있게 한다. 그리고, 제안 모델은 기존 변형모델에서 포함하는 내부 힘(internal force)과 외부 힘(external force)외에 자체교차방지 힘(non-self-intersection force)을 추가함으로서 효과적으로 모델내의 자체교차를 방지할 수 있게 하였다.

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A Study on Composite Filter for AWGN Removal (AWGN 제거를 위한 합성 필터에 관한 연구)

  • Kwon, Se-Ik;Hwang, Yeong-Yeun;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.684-686
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    • 2017
  • Currently, image processing is used in various fields including military, medical and industrial fields. Noise added to images undermine the quality of images. As such, the removal of noise is an essential step to process images such as through recognition of images, detection of edge and segmentation of images. Studies on removing noise from images are actively being undertaken. One of the leading noises that are added to images is the AWGN(additive white Gaussian noise). This paper suggests an algorithm that synthesizes a filter that uses edge detection and standard deviation to ease AWGN.

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Assessment of Attenuation Correction Algorithms With a $^{137}$Cs Point Source (Cs-137 점선원을 이용한 감쇠보정기법들에 대한 평가)

  • Bong, Jung-Kyun;Kim, Hee-Joung;Park, Hae-Jung;Kwon, Yun-Youn;Son, Hye-Kyoung;Yun, Mi-Jin;Lee, Jong-Doo;Jung, Hae-Jo
    • Proceedings of the Korean Society of Medical Physics Conference
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    • 2004.11a
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    • pp.96-99
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    • 2004
  • The objective of this study is to assess attenuation correction algorithms utilized in a multipurpose whole-body GSO PET scanner. Four different types of phantoms were tested using different types of attenuation correction techniques. FOV (Field of View) of 256mm was used for brain PET imaging. For compensating attenuation, transmission data of a $^{137}$Cs point source were acquired after the F-18 emission source was infused to the phantoms. Scatter correction were peformed. Reconstructed images of the phantoms were assessed. In addition, reconstructed images of a normal subject were compared and assessed by nuclear medicine physicians. As a result, decreased intensity at the central portion of the attenuation map with cylindrical phantom was noticed during use of the measured attenuation correction. On the other hand, segmentation or remapping attenuation correction provided uniform phantom image. the images reconstructed from the clinical brain data explained the attenuation of a skull, at though reconstructed images of the phantoms couldn't explain it. in conclusion, the complicated and improved attenuation correction methods were required to obtain the better accuracy of the quantitative brain PET images. Our study will be useful in improving quantitative brain PET imaging modalities with attenuation correction of $^{137}$Cs transmission source.

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Topology Correction for Flattening of Brain Cortex

  • Kwon Min Jeong;Park Hyun Wook
    • Journal of Biomedical Engineering Research
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    • v.26 no.2
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    • pp.73-86
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    • 2005
  • We need to flatten the brain cortex to smooth surface, sphere, or 2D plane in order to view the buried sulci. The rendered 3D surface of the segmented white matter and gray matter does not have the topology of a sphere due to the partial volume effect and segmentation error. A surface without correct topology may lead to incorrect interpretation of local structural relationships and prevent cortical unfolding. Although some algorithms try to correct topology, they require heavy computation and fail to follow the deep and narrow sulci. This paper proposes a method that corrects topology of the rendered surface fast, accurately, and automatically. The proposed method removes fractions beside the main surface, fills cavities in the inside of the main surface, and removes handles in the surface. The proposed method to remove handles has three-step approach. Step 1 performs smoothing operation on the rendered surface. In Step 2, vertices of sphere are gradually deformed to the smoothed surfaces and finally to the boundary of the segmented white matter and gray matter. The Step 2 uses multi-resolutional approach to prevent the deep sulci from geometrical intersection. In Step 3, 3D binary image is constructed from the deformed sphere of Step 2 and 3D surface is regenerated from the 3D binary image to remove intersection that may happen. The experimental results show that the topology is corrected while principle sulci and gyri are preserved and the computation amount is acceptable.

Automatic Liver Segmentation of a Contrast Enhanced CT Image Using a Partial Histogram Threshold Algorithm (부분 히스토그램 문턱치 알고리즘을 사용한 조영증강 CT영상의 자동 간 분할)

  • Kyung-Sik Seo;Seung-Jin Park;Jong An Park
    • Journal of Biomedical Engineering Research
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    • v.25 no.3
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    • pp.189-194
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    • 2004
  • Pixel values of contrast enhanced computed tomography (CE-CT) images are randomly changed. Also, the middle liver part has a problem to segregate the liver structure because of similar gray-level values of a pancreas in the abdomen. In this paper, an automatic liver segmentation method using a partial histogram threshold (PHT) algorithm is proposed for overcoming randomness of CE-CT images and removing the pancreas. After histogram transformation, adaptive multi-modal threshold is used to find the range of gray-level values of the liver structure. Also, the PHT algorithm is performed for removing the pancreas. Then, morphological filtering is processed for removing of unnecessary objects and smoothing of the boundary. Four CE-CT slices of eight patients were selected to evaluate the proposed method. As the average of normalized average area of the automatic segmented method II (ASM II) using the PHT and manual segmented method (MSM) are 0.1671 and 0.1711, these two method shows very small differences. Also, the average area error rate between the ASM II and MSM is 6.8339 %. From the results of experiments, the proposed method has similar performance as the MSM by medical Doctor.

Theoretical Investigation of Metal Artifact Reduction Based on Sinogram Normalization in Computed Tomography (컴퓨터 단층영상에서 사이노그램 정규화를 이용한 금속 영상왜곡 저감 방법의 이론적 고찰)

  • Jeon, Hosang;Youn, Hanbean;Nam, Jiho;Kim, Ho Kyung
    • Progress in Medical Physics
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    • v.24 no.4
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    • pp.303-314
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    • 2013
  • Image quality of computed tomography (CT) is very vulnerable to metal artifacts. Recently, the thickness and background normalization techniques have been introduced. Since they provide flat sinograms, it is easy to determine metal traces and a simple linear interpolation would be enough to describe the missing data in sinograms. In this study, we have developed a theory describing two normalization methods and compared two methods with respect to various sizes and numbers of metal inserts by using simple numerical simulations. The developed theory showed that the background normalization provide flatter sinograms than the thickness normalization, which was validated with the simulation results. Numerical simulation results with respect to various sizes and numbers of metal inserts showed that the background normalization was better than the thickness normalization for metal artifact corrections. Although the residual artifacts still existed, we have showed that the background normalization without the segmentation procedure was better than the thickness normalization for metal artifact corrections. Since the background normalization without the segmentation procedure is simple and it does not require any users' intervention, it can be readily installed in conventional CT systems.

Prognostic Value of Sarcopenia and Myosteatosis in Patients with Resectable Pancreatic Ductal Adenocarcinoma

  • Dong Wook Kim;Hyemin Ahn;Kyung Won Kim;Seung Soo Lee;Hwa Jung Kim;Yousun Ko;Taeyong Park;Jeongjin Lee
    • Korean Journal of Radiology
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    • v.23 no.11
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    • pp.1055-1066
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    • 2022
  • Objective: The clinical relevance of myosteatosis has not been well evaluated in patients with pancreatic ductal adenocarcinoma (PDAC), although sarcopenia has been extensively researched. Therefore, we evaluated the prognostic value of muscle quality, including myosteatosis, in patients with resectable PDAC treated surgically. Materials and Methods: We retrospectively evaluated 347 patients with resectable PDAC who underwent curative surgery (mean age ± standard deviation, 63.6 ± 9.6 years; 202 male). Automatic muscle segmentation was performed on preoperative computed tomography (CT) images using an artificial intelligence program. A single axial image of the portal phase at the inferior endplate level of the L3 vertebra was used for analysis in each patient. Sarcopenia was evaluated using the skeletal muscle index, calculated as the skeletal muscle area (SMA) divided by the height squared. The mean SMA attenuation was used to evaluate myosteatosis. Diagnostic cutoff values for sarcopenia and myosteatosis were devised using the Contal and O'Quigley methods, and patients were classified according to normal (nMT), sarcopenic (sMT), myosteatotic (mMT), or combined (cMT) muscle quality types. Multivariable Cox regression analyses were conducted to assess the effects of muscle type on the overall survival (OS) and recurrence-free survival (RFS) after surgery. Results: Eighty-four (24.2%), 73 (21.0%), 75 (21.6%), and 115 (33.1%) patients were classified as having nMT, sMT, mMT, and cMT, respectively. Compared to nMT, mMT and cMT were significantly associated with poorer OS, with hazard ratios (HRs) of 1.49 (95% confidence interval, 1.00-2.22) and 1.68 (1.16-2.43), respectively, while sMT was not (HR of 1.40 [0.94-2.10]). Only mMT was significantly associated with poorer RFS, with an HR of 1.59 (1.07-2.35), while sMT and cMT were not. Conclusion: Myosteatosis was associated with poor OS and RFS in patients with resectable PDAC who underwent curative surgery.

Develop 3D Prostate Cancer Visualization Tool in Smart Care System (스마트 케어 시스템에서의 3차원 전립선 암 가시화 도구 개발)

  • Ahn, Byung Uk;Shin, Seung Won;Choi, Moon Hyung;Jung, Seung Eun;Kim, Kwang Gi
    • Journal of Korea Multimedia Society
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    • v.19 no.2
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    • pp.163-169
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    • 2016
  • In Korea, prostate cancer accounted for generating growth rate second the following thyroid cancer, because of western dietary habits. Survival rate of prostate cancer after clinical behavior is changed depend on follow-up management. A telemedicine have been applied to replacement of medical specialist in rural area, and a quick reaction to emergency situation. Our study developed prostate 3-dimensional (3D) visualization program and designed prostate aftercare system architecture, called smart care, using a device that can access the Internet. Region of interest (ROI) in prostate was manually segmented by physicians and visualized to 3D objects and sent to PACS Server as DICOM images. So, medical personnel could confirm patients' data along with 3D images not only PACS system, but also portable device like a smart phone. As a result, we conducted the aftercare service to 98 patients and visualize 3D prostate images. 3D images had advantage to instinctively apprehend where lesion is and make patients to understand state of their disease easily. In the future, should conduct an aftercare service to more patients, and will obtain numerical index through follow-up study to an accurate analysis.

Generation Method of 3D Human Body Level-of-Detail Model for Virtual Reality Device using Tomographic Image (가상현실 장비를 위한 단층 촬영 영상 기반 3차원 인체 상세단계 모델 생성 기법)

  • Wi, Woochan;Heo, Yeonjin;Lee, Seongjun;Kim, Jion;Shin, Byeong-Seok;Kwon, Koojoo
    • The Journal of Korean Institute of Next Generation Computing
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    • v.15 no.4
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    • pp.40-50
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    • 2019
  • In recent years, it is important to visualize an accurate human body model for the low-end system in the medical imaging field where augmented reality technology and virtual reality technology are used. Decreasing the geometry of a model causes a difference from the original shape and considers the difference as an error. So, the error should be minimized while reducing geometry. In this study, the organ areas of a human body in the tomographic images such as CT or MRI is segmented and 3D geometric model is generated, thereby implementing the reconstruction method of multiple resolution level-of-detail model. In the experiment, a virtual reality platform was constructed to verify the shape of the reconstructed model, targeting the spine area. The 3D human body model and patient information can be verified using the virtual reality platform.

Reversible Watermarking based on Predicted Error Histogram for Medical Imagery (의료 영상을 위한 추정오차 히스토그램 기반 가역 워터마킹 알고리즘)

  • Oh, Gi-Tae;Jang, Han-Byul;Do, Um-Ji;Lee, Hae-Yeoun
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.5
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    • pp.231-240
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    • 2015
  • Medical imagery require to protect the privacy with preserving the quality of the original contents. Therefore, reversible watermarking is a solution for this purpose. Previous researches have focused on general imagery and achieved high capacity and high quality. However, they raise a distortion over entire image and hence are not applicable to medical imagery which require to preserve the quality of the objects. In this paper, we propose a novel reversible watermarking for medical imagery, which preserve the quality of the objects and achieves high capacity. First, object and background region is segmented and then predicted error histogram-based reversible watermarking is applied for each region. For the efficient watermark embedding with small distortion in the object region, the embedding level at object region is set as low while the embedding level at background region is set as high. In experiments, the proposed algorithm is compared with the previous predicted error histogram-based algorithm in aspects of embedding capacity and perceptual quality. Results support that the proposed algorithm performs well over the previous algorithm.