• 전기학회논문지
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• 제66권8호
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• pp.1272-1277
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• 2017

To assist radiologists for the characterization of breast masses, Computer-aided Diagnosis(CADx) system has been studied. The CADx system can improve the diagnostic accuracy of radiologists by providing objective information about breast masses. Morphological and texture features were extracted from the breast ultrasound images. Based on extracted features, the CADx system retrieves masses that are similar to a query mass from a reference library using a k-nearest neighbor (k-NN) approach. Eight similarity measures of distance, Euclidean, Chebyshev(Minkowski family), Canberra, Lorentzian($F_2$ family), Wave Hedges, Motyka(Intersection family), and Cosine, Dice(Inner Product family) are evaluated by ROC(Receiver Operating Characteristic) analysis. The Inner Product family measure used with the k-NN classifier provided slightly higher performance for classification of malignant and benign masses than those with the Minkowski, $F_2$, and Intersection family measures.

• International journal of advanced smart convergence
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• 제8권1호
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• pp.24-34
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• 2019

In this research, a practical deep learning framework to differentiate the lesions and nodules in breast acquired with ultrasound imaging has been proposed. 7408 ultrasound breast images of 5151 patient cases were collected. All cases were biopsy proven and lesions were semi-automatically segmented. To compensate for the shift caused in the segmentation, the boundaries of each lesion were drawn using Fully Convolutional Networks(FCN) segmentation method based on the radiologist's specified point. The data set consists of 4254 benign and 3154 malignant lesions. In 7408 ultrasound breast images, the number of training images is 6579, and the number of test images is 829. The margin between the boundary of each lesion and the boundary of the image itself varied for training image augmentation. The training images were augmented by varying the margin between the boundary of each lesion and the boundary of the image itself. The images were processed through histogram equalization, image cropping, and margin augmentation. The networks trained on the data with augmentation and the data without augmentation all had AUC over 0.95. The network exhibited about 90% accuracy, 0.86 sensitivity and 0.95 specificity. Although the proposed framework still requires to point to the location of the target ROI with the help of radiologists, the result of the suggested framework showed promising results. It supports human radiologist to give successful performance and helps to create a fluent diagnostic workflow that meets the fundamental purpose of CADx.

• 대한핵의학회지
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• 제36권3호
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• pp.177-184
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• 2002

목적: 원발성 유방암을 진단하는데 있어서 유방초음파검사와 $^{99m}-Tc-MIBI$ 유방스캔이 유용하다고 평가받고 있다. 그러나 유방초음파 검사는 특이도가 낮다는 문제점을 가지고 있다. 이에 본 연구에서는 유방암 진단에 있어서의 유방초음파 검사와 $^{99m}-Tc-MIBI$ 유방스캔의 진단적인 유용성을 비교해 보았다. 대상 및 방법: 본 연구에서는 1999년에서 2000년 사이에 의심되는 유방 종물에 대해서 유방초음파검사와 $^{99m}-Tc-MIBI$ 유방스캔을 시행했던 174명의 환자를 대상으로 하였다. 모든 환자의 병리조직학적인 결과는 수술이나 미세흡인세포진 검사에 의해서 얻어졌다. 결과: 174명의 환자 중에서 악성질환으로 진단받은 경우는 117명이었고, 양질환성으로 진단받은 경우는 37명이었다. 유방초음파 검사의 판독은 88명의 진양성, 9명의 위음성, 8명의 위양성, 34명의 진음성, 그리고 35명의 미확정의 결과를 보여주었다. $^{99m}-Tc-MIBI$ 유방스캔의 판독은 91명의 진양성, 26명의 위음성, 9명의 위양성, 그리고 48명의 진음성의 결과를 보여주었다. 유방초음파 검사에 의한 민감도, 특이도, 양성예측율, 음성예측율은 각각 66.7%, 44.2%, 67.2%, 그리고. 43.6%였다. $^{99m}-Tc-MIBI$ 유방스캔에 의한 민감도, 특이도, 양성예측율, 음성예측율은 각각 77.8%, 84.2%, 91% 그리고 64.9%였다. 유방초음파 검사에 의해서 미확정으로 판독된 35명의 환자에 대해서 $^{99m}-Tc-MIBI$ 유방스캔은 13명의 진양성, 15명의 진음성, 그리고 7명의 위양성의 결과를 보여주었다. 결론: 원발성 유방암을 진단하는데 있어서 유방초음파 검사보다 $^{99m}-Tc-MIBI$ 유방스캔의 민감도와 특이도가 훨씬 더 높고, 유방초음파 검사에 의해서 정확히 결론지을 수 없었던 경우에도 $^{99m}-Tc-MIBI$ 유방스캔은 훨씬 더 유용한 정보를 제공해 준다.

• 대한방사선기술학회지:방사선기술과학
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• 제31권1호
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• pp.61-69
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• 2008

유방초음파 검사는 유방암 검사에 있어 유방촬영술에 비하여 많은 장점이 있으나, 미세석회화 발견에는 적합하지 않은 단점이 있다. 이에 유방초음파 검사에서 기존의 7.5 MHz 선형 탐촉자를 사용하여 매질의 공명현상을 이용한 유방조직 석회화 병변을 관측할 수 있는 방법을 연구하였다. 먼저 gelatin과 돼지 젖가슴살을 이용하여 유방조직 팬텀을 제작하였으며, 외부 진동을 변화시켜 가며 석회화 병변을 관측하였다. 유방조직 팬텀안에 주입된 석회화는 주변 조직과 다른 공명을 일으키면서 외부진동에 따라 음향공명의 정도가 파워도플러의 ROI 영역 내의 색상의 밝기와 영역의 차이로 나타내었다. 낮은 주파수 영역에는 음향공명이 거의 나타나지 않았으며, 약 $300{\sim}400\;Hz$ 사이에서 일정한 플래토우 영역을 나타내었으며, 이후 주파수가 증가함에 따라 색상이 사라짐을 확인하였다.

• 산업공학
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• 제21권4호
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• pp.394-402
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• 2008

The objective of this paper is to design segmentation algorithm for applying the breast ultrasound image to CAD(Computer Aided Diagnosis). This study is conducted after understanding limits, used algorithm and demands of CAD system by interviewing with a medical doctor and analyzing related works based on a general CAD framework that is consisted of five step-establishment of plan, analysis of needs, design, implementation and test & maintenance. Detection function of CAD is accomplished by Canny algorithm and arithmetic operations for segmentation. In addition to, long computing time is solved by extracting ROI (Region Of Interests) and applying segmentation technical methods based morphology algorithm. Overall course of study is conducted by verification of medical doctor. And validity and verification are satisfied by medical doctor's confirmation. Moreover, manual segmentation of related works, restrictions on the number of tumor and dependency of image resolution etc. was solved. This study is utilized as a support system aided doctors' subjective diagnosis even though a lot of future studies is needed for entire application of CAD system.

• 산업경영시스템학회지
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• 제31권1호
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• pp.74-82
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• 2008

The objective of this paper is to remove noises of image based on the heuristic noises filter and to extract a tumor region by using morphology techniques in breast ultrasound image. Similar objective studies have been conducted based on ultrasound image of high resolution. As a result, efficiency of noise removal is not fine enough for low resolution image. Moreover, when ultrasound image has multiple tumors, the extraction of ROI (Region Of Interest) is not accomplished or processed by a manual selection. In this paper, our method is done 4 kinds of process for noises removal and the extraction of ROI for solving problems of restrictive automated segmentation. First process is that pixel value is acquired as matrix type. Second process is a image preprocessing phase that is aimed to maximize a contrast of image and prevent a leak of personal information. In next process, the heuristic noise filter that is based on opinion of medical specialist is applied to remove noises. The last process is to extract a tumor region by using morphology techniques. As a result, the noise is effectively eliminated in all images and a extraction of tumor regions is possible though one ultrasound image has several tumors.

• Korean Journal of Radiology
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• 제24권4호
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• pp.274-283
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• 2023

Objective: To compare the outcomes of digital breast tomosynthesis (DBT) screening combined with ultrasound (US) with those of digital mammography (DM) combined with US in women with dense breasts. Materials and Methods: A retrospective database search identified consecutive asymptomatic women with dense breasts who underwent breast cancer screening with DBT or DM and whole-breast US simultaneously between June 2016 and July 2019. Women who underwent DBT + US (DBT cohort) and DM + US (DM cohort) were matched using 1:2 ratio according to mammographic density, age, menopausal status, hormone replacement therapy, and a family history of breast cancer. The cancer detection rate (CDR) per 1000 screening examinations, abnormal interpretation rate (AIR), sensitivity, and specificity were compared. Results: A total of 863 women in the DBT cohort were matched with 1726 women in the DM cohort (median age, 53 years; interquartile range, 40-78 years) and 26 breast cancers (9 in the DBT cohort and 17 in the DM cohort) were identified. The DBT and DM cohorts showed comparable CDR (10.4 [9 of 863; 95% confidence interval {CI}: 4.8-19.7] vs. 9.8 [17 of 1726; 95% CI: 5.7-15.7] per 1000 examinations, respectively; P = 0.889). DBT cohort showed a higher AIR than the DM cohort (31.6% [273 of 863; 95% CI: 28.5%-34.9%] vs. 22.4% [387 of 1726; 95% CI: 20.5%-24.5%]; P < 0.001). The sensitivity for both cohorts was 100%. In women with negative findings on DBT or DM, supplemental US yielded similar CDRs in both DBT and DM cohorts (4.0 vs. 3.3 per 1000 examinations, respectively; P = 0.803) and higher AIR in the DBT cohort (24.8% [188 of 758; 95% CI: 21.8%-28.0%] vs. 16.9% [257 of 1516; 95% CI: 15.1%-18.9%; P < 0.001). Conclusion: DBT screening combined with US showed comparable CDR but lower specificity than DM screening combined with US in women with dense breasts.

• 대한방사선기술학회지:방사선기술과학
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• 제38권3호
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• pp.213-220
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• 2015

본 연구는 3차원 입체정위 유방생검술의 정확도를 알아보고, 심부침생검을 이용하여 Stereotactic biopsy과 Sonoguided biopsy의 정확도와 정밀도를 평가하고자 한다. Stereotactic QC phantom을 이용하여 실제 5개의 target 위치로 3D sterotactic machine의 정확도를 측정하고, CT장비로 Scan하여 실측을 구해 X, Y, Z의 길이의 정밀도를 비교한다. 유방조직과 유사하게 제작한 Agar power phantom을 이용하여 5개의 각기 다른 needle tip Target을 통해 3D sterotactic machine과 2D ultrasound machine의 정확도를 비교하고, Z축을 장비별로 실측하여 정밀도와 신뢰도를 비교하며, 6개의 모조병소 Target을 심어놓은 Medical application phantom으로 표적하여 육안검사와 Specimen검사를 통해 정확도를 확인하였다. Stereotactic QC phantom으로 측정한 3D sterotactic machine의 정확도는 100%였으며, CT와 비교한 정밀도는 X, Y, Z축이 모두 p>0.05로 나타났다. Agar powder phantom으로 측정한 두 장비의 정확도는 100%의 정확도를 보였으며, CT와 두 장비 사이에는 p > 0.05로 차이가 없었다. 그러나 2명의 방사선사가 측정한 신뢰도분석에서 3D sterotactic machine은 ICC가 0.954였고, 2D ultrasound machine은 0.785로 2D ultrasound machine이 술자에 따라 차이가 있었다. Medical application phantom의 실험에서 3D sterotactic machine은 Sliced boneless ham을, 2D ultrasound machine은 small chalk powder group를 찾을 수 없었다. Phantom을 이용한 3차원 입체정위 유방생검술의 정확성은 우수하게 나타났고, 인체조직과 비슷한 Agar powder phantom과 유방 조직과 비슷한 Medical application phantom을 이용하여 Stereotactic biopsy과 Sonoguided biopsy의 정확도와 정밀도 모두 우수하게 나타났다. 또한 Medical application phantom의 심부침생검의 정확성 평가에서 각 검사에 따라 생검 표본이 병소의 형태에 따라 상이하게 채취되었고, 3차원 입체정위 유방생검술의 재현성이 유방 초음파검사보다 술자의 영향없이 우수하였다.

• 전기의세계
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• 제66권8호
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• pp.33-35
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• 2017

• Investigative Magnetic Resonance Imaging
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• 제26권2호
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• pp.135-149
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• 2022

Purpose: To assess clinically significant imaging findings of malignant intramammary lymph nodes (IMLNs) in breast cancer patients and to evaluate their diagnostic performance in predicting malignant IMLN. Materials and Methods: A total of 110 cases with IMLN of BI-RADS category 3 or more, not typical benign IMLN, in MR of breast cancer patients between January 2016 and January 2021 were retrospectively reviewed. After excluding 33 cases, 77 cases were finally included. Among them, 58 and 19 were confirmed as benign and malignant, respectively. Qualitative and quantitative MR imaging features of the IMLN were retrospectively analyzed. Sizes and final assessment categories of IMLN on MRI, mammography, and ultrasound were reviewed. Diagnostic performances of imaging features on MRI, mammography, and ultrasound were then evaluated. Results: For qualitative MR features, shape, margin, and preserved central hilum were significantly different between benign and malignant groups (P < 0.05). For quantitative MR features, long diameter over 6 mm, short diameter over 4 mm, and cortical thickening over 3 mm showed high sensitivities in predicting malignant IMLNs (89.5%, 94.7%, and 100%, respectively). Size exceeding 1 cm showed high specificity and accuracy in predicting malignant IMLN on MR, mammography, and ultrasound (91.4% and 80.5%; 96.6% and 79.25; 98.3% and 80.5%, respectively). Conclusion: Various MR imaging features and size can be helpful for predicting malignant IMLN in breast cancer patients.