• Title/Summary/Keyword: medical image analysis

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Impact of the Liver Imaging Reporting and Data System on Research Studies of Diagnosing Hepatocellular Carcinoma Using MRI

  • Yura Ahn;Sang Hyun Choi;Jong Keon Jang;So Yeon Kim;Ju Hyun Shim;Seung Soo Lee;Jae Ho Byun
    • Korean Journal of Radiology
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    • v.23 no.5
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    • pp.529-538
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    • 2022
  • Objective: Since its introduction in 2011, the CT/MRI diagnostic Liver Imaging Reporting and Data System (LI-RADS) has been updated in 2014, 2017, and 2018. We evaluated the impact of CT/MRI diagnostic LI-RADS on liver MRI research methodology for the diagnosis of hepatocellular carcinoma (HCC). Materials and Methods: The MEDLINE, EMBASE, and Cochrane databases were searched for original articles reporting the diagnostic performance of liver MRI for HCC between 2011 and 2019. The MRI techniques, image analysis methods, and diagnostic criteria for HCC used in each study were investigated. The studies were classified into three groups according to the year of publication (2011-2013, 2014-2016, and 2017-2019). We compared the percentage of studies adopting MRI techniques recommended by LI-RADS, image analysis methods in accordance with the lexicon defined in LI-RADS, and diagnostic criteria endorsed by LI-RADS. We compared the pooled sensitivity and specificity between studies that used the LI-RADS and those that did not. Results: This systematic review included 179 studies. The percentages of studies using imaging techniques recommended by LI-RADS were 77.8% for 2011-2013, 85.7% for 2014-2016, and 84.2% for 2017-2019, with no significant difference (p = 0.951). After the introduction of LI-RADS, the percentages of studies following the LI-RADS lexicon were 0.0%, 18.4%, and 56.6% in the respective periods (p < 0.001), while the percentages of studies using the LI-RADS diagnostic imaging criteria were 0.0%, 22.9%, and 60.7%, respectively (p < 0.001). Studies that did not use the LI-RADS and those that used the LIRADS version 2018 showed no significant difference in sensitivity and specificity (86.3% vs. 77.7%, p = 0.102 and 91.4% vs. 89.9%, p = 0.770, respectively), with some difference in heterogeneity (I2 = 94.3% vs. 86.7% in sensitivity and I2 = 86.6% vs. 53.2% in specificity). Conclusion: LI-RADS imparted significant changes in the image analysis methods and diagnostic criteria used in liver MRI research for the diagnosis of HCC.

Multimodal Digital Photographic Imaging System for Total Diagnostic Analysis of Skin Lesions: DermaVision-Pro (다모드 디지털 사진 영상 시스템을 이용한 피부 손상의 진단적 분석에 대한 연구 : DermaVision-Pro)

  • Bae, Young-Woo;Kim, Eun-Ji;Jung, Byung-Jo
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.153-154
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    • 2008
  • Digital photographic analysis is currently considered as a routine procedure in clinic because periodic follow-up examinations can provide meaningful information for diagnosis. However, it is impractical to separately evaluate all suspicious lesions with conventional digital photographic systems, which have inconsistent characteristics of the environmental conditions. To address the issue, it is necessary for total diagnostic evaluation in clinic to integrate conventional systems. Previously, a multimodal digital photographic imaging system, which provides a conventional color image, parallel and cross polarization color images and a fluorescent color image, was developed for objective evaluation of facial skin lesions. Based on our previous study, we introduce a commercial product, "DermaVision-PRO," for routine use in clinical application in dermatology. We characterize the system and describe the image analysis methods for objective evaluation of skin lesions. In order to demonstrate the validity of the system in dermatology, sample images were obtained from subjects with various skin disorders, and image analysis methods were applied for objective evaluation of those lesions.

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An Adaptive Histogram Equalization Based Local Technique for Contrast Preserving Image Enhancement

  • Lee, Joonwhoan;Pant, Suresh Raj;Lee, Hee-Sin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.1
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    • pp.35-44
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    • 2015
  • The main purpose of image enhancement is to improve certain characteristics of an image to improve its visual quality. This paper proposes a method for image contrast enhancement that can be applied to both medical and natural images. The proposed algorithm is designed to achieve contrast enhancement while also preserving the local image details. To achieve this, the proposed method combines local image contrast preserving dynamic range compression and contrast limited adaptive histogram equalization (CLAHE). Global gain parameters for contrast enhancement are inadequate for preserving local image details. Therefore, in the proposed method, in order to preserve local image details, local contrast enhancement at any pixel position is performed based on the corresponding local gain parameter, which is calculated according to the current pixel neighborhood edge density. Different image quality measures are used for evaluating the performance of the proposed method. Experimental results show that the proposed method provides more information about the image details, which can help facilitate further image analysis.

A standardization model based on image recognition for performance evaluation of an oral scanner

  • Seo, Sang-Wan;Lee, Wan-Sun;Byun, Jae-Young;Lee, Kyu-Bok
    • The Journal of Advanced Prosthodontics
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    • v.9 no.6
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    • pp.409-415
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    • 2017
  • PURPOSE. Accurate information is essential in dentistry. The image information of missing teeth is used in optically based medical equipment in prosthodontic treatment. To evaluate oral scanners, the standardized model was examined from cases of image recognition errors of linear discriminant analysis (LDA), and a model that combines the variables with reference to ISO 12836:2015 was designed. MATERIALS AND METHODS. The basic model was fabricated by applying 4 factors to the tooth profile (chamfer, groove, curve, and square) and the bottom surface. Photo-type and video-type scanners were used to analyze 3D images after image capture. The scans were performed several times according to the prescribed sequence to distinguish the model from the one that did not form, and the results confirmed it to be the best. RESULTS. In the case of the initial basic model, a 3D shape could not be obtained by scanning even if several shots were taken. Subsequently, the recognition rate of the image was improved with every variable factor, and the difference depends on the tooth profile and the pattern of the floor surface. CONCLUSION. Based on the recognition error of the LDA, the recognition rate decreases when the model has a similar pattern. Therefore, to obtain the accurate 3D data, the difference of each class needs to be provided when developing a standardized model.

Recognizing asymmetric moire patterns for human spinal deformity detection

  • Kim, Hyoung-Seop;Hiroshi UENO;Seiji ISHIKAWA;Yoshinori Otsuka
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.568-571
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    • 1997
  • Recently, the number of techniques for analyzing medical images has been increasing in computer vision, employing X-ray CT images, ultrasound images, MR images, moire topographic images, etc. Spinal deformity is a serious problem especially for teenagers and medical doctors inspect moire topographic images of their backs visually for the primary screening. If a subject is normal, the moire image is almost symmetric with respect to the middle line of the subject's back, otherwise it shows asymmetric shape. In this paper, an image analysis technique is described for discriminating suspicious cases from normal in human spinal deformity by recognizing asymmetric moire images of human backs. The principal axes which are sensitive to asymmetry of the moire image are extracted at two parts on a subject's back and their angles are evaluated with respect to the detected middle line of the back. The two angles compose a 2-D feature space and inspected cases are divided into two clusters in the space by a linear discriminant function based on the Mahalanobis distance. Given 120 cases, 60 normal and 60 abnormal, the leave-out method was applied for the recognition and 75% recognition rate was achieved.

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Medical Image Segmentation: A Comparison Between Unsupervised Clustering and Region Growing Technique for TRUS and MR Prostate Images

  • Ingale, Kiran;Shingare, Pratibha;Mahajan, Mangal
    • International Journal of Computer Science & Network Security
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    • v.21 no.5
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    • pp.1-8
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    • 2021
  • Prostate cancer is one of the most diagnosed malignancies found across the world today. American cancer society in recent research predicted that over 174,600 new prostate cancer cases found and nearly 31,620 death cases recorded. Researchers are developing modest and accurate methodologies to detect and diagnose prostate cancer. Recent work has been done in radiology to detect prostate tumors using ultrasound imaging and resonance imaging techniques. Transrectal ultrasound and Magnetic resonance images of the prostate gland help in the detection of cancer in the prostate gland. The proposed paper is based on comparison and analysis between two novel image segmentation approaches. Seed region growing and cluster based image segmentation is used to extract the region from trans-rectal ultrasound prostate and MR prostate images. The region of extraction represents the abnormality area that presents in men's prostate gland. Detection of such abnormalities in the prostate gland helps in the identification and treatment of prostate cancer

Study on the PET image quality according to various scintillation detectors based on the Monte Carlo simulation

  • Eunsoo Kim;Chanrok Park
    • The Korean Journal of Nuclear Medicine Technology
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    • v.27 no.2
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    • pp.129-132
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    • 2023
  • Purpose: Positron emisson tomography (PET) is a crucial medical imaging scanner for the detection of cancer lesions. In order to maintain the improved image quality, it is crucial to apply detectors of superior performance. Therefore, the purpose of this study was to compare PET image quality using Monte Carlo simulation based on the detector materials of BGO, LSO, and LuAP. Materials and Methods: The Geant4 Application for Tomographic Emission (GATE) was used to design the PET detector. Scintillations with BGO, LSO and LuAP were modelled, with a size of 3.95 × 5.3 mm2 (width × height) and 25.0 mm (thickness). The PET detector consisted of 34 blocks per ring and a total of 4 rings. A line source of 1 MBq was modelled and acquired with a radius of 1 mm and length of 20 mm for 20 seconds. The acquired image was reconstructed maximum likelihood expectation maximization with 2 iteration and 10 subsets. The count comparison was carried out. Results and Discussion: The highest true, random, and scatter counts were obtained from the BGO scintillation detector compared to LSO and LuAP. Conclusion: The BGO scintillation detector material indicated excellent performance in terms of detection of gamma rays from emitted PET phantom.

Fluorescence Molecular Imaging

  • Choi, Heung-Kook;Ntziachristos, Vasilis;Weissleder, Ralph
    • Proceedings of the KSMRM Conference
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    • 2004.09a
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    • pp.23-32
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    • 2004
  • The chemotherapy sensitive Lewis lung carcinoma (LLC) and chemotherapy resistant Lewis lung carcinoma (CR-LLC) tumors concurrently implanted in mice, and compare these findings with histological macroscopic observations against 3D reconstruction of Fluorescence Molecular Tomography (FMT) preformed in vivo on the same animals. For the 3D image reconstruction we used 32 laser source images, a flat image and 3D surface rendering that confused for 3D Fluorescence Molecular Imaging (FMI). A minimum of ten tissue sections were analyzed per tumor for quantification of the TUNEL-positive cells, cell-associated Cy5.5-Annexin and vessel-associated Alexa Fluor-Lectin. These are useful apoptosis and angiogenesis markers, and they serve as validation experiments to data obtained in vivousing a Cy5.5-Annexin V conjugate injected intravenously in chemotherapy-treated animals carrying the tumors studied histologically. We detected higher levels of apoptosis and corresponding higher levels of Cy5.5 fluorescence in the LLC vs. the CR-LLC tumors according to tissue depth and these findings confirm that in vivo staining with the Cy5.5-Annexing conjugate correlates well with in vitro TUNEL staining and is consistent with the higher apoptotic index expected from the LLC line. There appeared to be 1.38% more apoptosis for LLC than CR-LLC. Consequently there is good correlation between the histology results and in vivo fluorescence-mediated optical imaging. In conclusion the apoptotic images of 3D FMI were validated by microscopic histological image analysis. This is a significant result for the continuous progress of fluorescence 3D imaging research.

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The Study of Edge Extract Methods Using Improved Detect Mask (개선된 검출 마스크를 이용한 에지추출 방법들에 관한 연구)

  • Shin, Choong-Ho
    • Journal of Korea Multimedia Society
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    • v.12 no.2
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    • pp.191-199
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    • 2009
  • In this paper, the improved edge extract methods is proposed in order to extract edge. For the correct and fast detect, the binary image using the threshold value is applied for a experiment. For the experimental analysis, we compare the existing edge methods with the improved methods. Hereby, the exist methods are the sobel, robert, and prewitt. and the improved methods use the existing methods which is applied mask variations. The merits of the improved mothods have a result of a little erosion, a apparent edge. Specially, we use the grey image of medical image for the experimental analysis and then apply threshold value for a result image. After that, we acquire a apparent edge. For a quantitative analysis of the each methods, the each images was applied a histogram. As a result, we prove the merit of the improved methods using a analytical graph of the medical images.

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Depending on PACS Operating System Differences Analysis of Usefulness of Lossless Compression Method in Medical Image Upload: SNR, CNR, Histogram Comparative Analysis (PACS운영 시스템 차이에 따른 의료 영상 업로드 시 무손실 압축 방식의 유용성 분석: SNR, CNR, Histogram 비교 분석을 중심으로)

  • Choi, Ji-An;Hwang, Jun-Ho;Lee, Kyung-Bae
    • The Journal of the Korea Contents Association
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    • v.18 no.3
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    • pp.299-308
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    • 2018
  • This study focused on the fact that medical images that are issued at different hospitals may affect image quality on PACS when different software is used. A university hospital image was copied to the DICOM file and registered on the PACS of the university hospital B. The capacity and image quality of the software used in the university hospital were evaluated by SNR, CNR and histogram. As the compression ratio increased, SNR and CNR tended to decrease. Note that Lossless Compression decreased the data size by half compared to No Compression, but SNR and CNR did not change. As a result of the histogram analysis, the information loss due to the underflow phenomenon was conspicuous. When moving to another hospital, No compression or lossless compression method should be used. In conclusion, it is useful to use the lossless compression method, considering waiting time and economic efficiency in uploading.