• Asian Pacific Journal of Cancer Prevention
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• 제17권3호
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• pp.1277-1284
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• 2016

Background: Early detection is a critical part of reducing the burden of breast cancer and breast self-examination (BSE) has been found to be an especially important early detection strategy in low and middle income countries such as Malaysia. Although reports indicate that Malaysian women report an increase in BSE activity in recent years, additional research is needed to explore factors that may help to increase this behavior among Southeastern Asian women. Objective: This study is the first of its kind to explore how the predicting variables of self-efficacy, perceived barriers, and body image factors correlate with self-reports of past BSE, and intention to conduct future breast self-exams among female students in Malaysia. Materials and Methods: Through the analysis of data collected from a prior study of female students from nine Malaysian universities (n=842), this study found that self-efficacy, perceived barriers and specific body image sub-constructs (MBSRQ-Appearance Scales) were correlated with, and at times predicted, both the likelihood of past BSE and the intention to conduct breast self-exams in the future. Results: Self-efficacy (SE) positively predicted the likelihood of past self-exam behavior, and intention to conduct future breast self-exams. Perceived barriers (BR) negatively predicted past behavior and future intention of breast self-exams. The body image sub-constructs of appearance evaluation (AE) and overweight preoccupation (OWP) predicted the likelihood of past behavior but did not predict intention for future behavior. Appearance orientation (AO) had a somewhat opposite effect: AO did not correlate with or predict past behavior but did correlate with intention to conduct breast self-exams in the future. The body image sub-constructs of body area satisfaction (BASS) and self-classified weight (SCW) showed no correlation with the subjects' past breast self-exam behavior nor with their intention to conduct breast self-exams in the future. Conclusions: Findings from this study indicate that both self-efficacy and perceived barriers to BSE are significant psychosocial factors that influence BSE behavior. These results suggest that health promotion interventions that help enhance self-efficacy and reduce perceived barriers have the potential to increase the intentions of Malaysian women to perform breast self-exams, which can promote early detection of breast cancers. Future research should evaluate targeted communication interventions for addressing self-efficacy and perceived barriers to breast self-exams with at-risk Malaysian women. and further explore the relationship between BSE and body image.

• Asian Pacific Journal of Cancer Prevention
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• 제17권6호
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• pp.2917-2921
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• 2016

Background: To explore factors that influence quality of life (QOL) in patients receiving breast conserving therapy (BCT). Materials and Methods: In this sequential mixed methods study, 118 women from Songklanagarind Hospital were included. We used participants' characteristics, Body Image Scale (BIS), and Functional Assessment of Cancer Therapy with the Breast Cancer Subscale (FACT-B) for analysis. The BIS transformed into presence of body image disturbance (BID). Factors that influenced QOL were determined by stepwise multiple linear regression. Forty-one participants were selected for qualitative analysis. Our female researcher performed the semi-structured interviews with questions based on the symbolic interaction theory. Final codes were analysed using thematic analysis along with investigator triangulation methods. Results: Ninety percent had early stage breast cancer with post-completed BCT, for an average of 2.7 years. The median BIS score and FACT-B score were 2 (IQR=10) and 130 (IQR=39). In the regression analysis, an age of more than 50 years and BID were significant factors. As for the value of conserved breasts, two themes emerged: a conserved breast is an essential part of a participant's life and also the representation of her womanhood; the importance of a breast is related to age. Conclusions: Body image influenced QOL in post BCT participants. The conserved breasts also lead to positive and better impact on their body image as an essential part of their life.

• 한국의류학회지
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• 제27권2호
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• pp.270-276
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• 2003

Methodology was suggested to analyze breast volume, base area of breast bulk. and surface area of breast using the 3D measurement system. Thirty-seven middle-aged (30s-40s) women wearing 80A brassiere were participated in this study. Image of the upper body was captured by Phase-shifting moire. The posture of the subject was adjusted to get the full image of the right breast. Rapidform 2001 was used for the analysis of the images. The mean breast volume was 547.0㎤ and mean base area of breast bulk was 235. I$\textrm{cm}^2$ It was also found that the volume(r=0.169) and surface area of breast(r=10.242) were loosely correlated with the circumference difference between top and under breast. Therefore, it is noted that current selection criterion of cup size based on the difference in the two kinds of breast circumference is inadequate. The result of this study is expected to contribute to the design of ergonomic brassiere as well as surgical operations in the medical field.

• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1363-1369
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• 2018

Breast cancer is one of the most common cancers in women worldwide. In Korea, breast cancer is most common cancer in women followed by thyroid cancer. The purpose of this study is to evaluate the possibility of using deep - run model for segmentation of breast masses and to identify the best deep-run model for breast mass segmentation. In this study, data of patients with breast masses were collected at Asan Medical Center. We used 596 images of mammography and 596 images of gold standard. In the area of interest of the medical image, it was cut into a rectangular shape with a margin of about 10% up and down, and then converted into an 8-bit image by adjusting the window width and level. Also, the size of the image was resampled to $150{\times}150$. In Deconvolution net, the average accuracy is 91.78%. In U-net, the average accuracy is 90.09%. Deconvolution net showed slightly better performance than U-net in this study, so it is expected that deconvolution net will be better for breast mass segmentation. However, because of few cases, there are a few images that are not accurately segmented. Therefore, more research is needed with various training data.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.655-657
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• 2021

인공지능 알고리즘을 이용한 유방암의 조기진단에 관련된 연구는 최근들어 활발하게 진행되고 있으나, 사용자의 목적에 맞는 처리속도 및 정확도 등에 다양한 한계점을 보인다. 이러한 문제를 해결하기 위해, 본 논문에서는 ImageNet에서 학습된 ResNet 모델을 현미경 기반 암세포 이미지에서 활용이 가능한 다단계 전이 학습을 제안하고, 이를 다시 전이 학습하여 초음파 유방암 영상을 양성 및 악성으로 분류하는 실험을 진행하였다. 제안된 다단계 전이 학습 알고리즘은 초음파 유방암 영상을 분류하였을 때 96% 이상의 정확도를 보였으며, 향후 암 세포주 및 실시간 영상처리 등의 추가를 통해 보다 높은 활용도와 정확도를 보일 것으로 기대한다.

• 기본간호학회지
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• 제18권3호
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• pp.328-336
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• 2011

Purpose: The purpose of this study was to identify the effects of cancer-overcome BeHaS exercise program on shoulder joint function, stress, body image and self-esteem in women who have had surgery for breast cancer. Method: A non-equivalent control group pre-post test design with an experimental group (n=25) and a control group (n=25) was used. The experimental group participated in the program once a week for eight weeks. Data were analyzed using descriptive statistics and Chi square and t-test with the SPSS Win 17.0. Results: There were significantly increased in shoulder joint function (p=.012), body image (p=.001), and self-esteem (p=.013), and significantly decreased in stress (p=.003). Conclusion: The results suggest that breast cancer-overcome BeHaS exercise program had beneficial effects on shoulder joint function, body image, self-esteem and stress in patients who have had surgery for breast cancer.

• 한국융합학회논문지
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• 제8권9호
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• pp.175-181
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• 2017

유방검사에서 영상의 진단 가치를 높일 수 있는 유방틀을 제작하여 유용성을 평가하고자 한다. 유리섬유강화플라스틱을 이용해서 유방틀을 제작하였다. 그리고 방사능계수율과 획득된 영상을 비교하였다. 유방틀의 평가에서 왼쪽과 오른쪽이 $1{\mu}Ci$ 당 counts가 각각 185 counts, 189 counts이다. 그리고 복와위 자세에서 획득된 영상은 원형에 가깝게 나타났다. 유방틀을 이용함으로써 진단 가치를 높일 수 있어 유방촬영 검사를 하는데 있어 유용할 것으로 사료된다.

• 지역사회간호학회지
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• 제23권4호
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• pp.405-414
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• 2012

Purpose: The purpose of this study was to examine the sexual maturation, body image, and self-esteem of Korean elementary school girls with symptoms of precocious puberty compared to those with no symptoms of precocious puberty. Methods: The subjects were 309 girls of lower grades in elementary school. Tanner's Sexual Maturation Rating (SMR), Self Image Scale, and Self-esteem Scale were utilized to determine the presence of symptoms of precocious puberty, body image, and self esteem. Collected data were analyzed by Chi-square test, independent t-test, and one-way ANOVA using the SPSS/WIN 17.0 program. Results: The percentage of the girls with breast development was 14.9%. Breast development usually began in the third grade (56.5%). Of the subjects, 0.3% were experiencing menstruation. Breast development was related to grade, age, height, weight, and a cause of worry. There was a significant difference of body image between girls with breast development in the first grade and in the second grade. Conclusion: An effective intervention that can improve the self-image of children with symptoms of precocious puberty should be developed to prevent and treat physical and mental problems related to sexual maturation.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1000-1011
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• 2021

In recent years, using Deep Learning methods to apply for medical and biomedical image analysis has seen many advancements. In clinical, using Deep Learning-based approaches for cancer image analysis is one of the key applications for cancer detection and treatment. However, the scarcity and shortage of labeling images make the task of cancer detection and analysis difficult to reach high accuracy. In 2015, the Unet model was introduced and gained much attention from researchers in the field. The success of Unet model is the ability to produce high accuracy with very few input images. Since the development of Unet, there are many variants and modifications of Unet related architecture. This paper proposes a new approach of using Unet++ with pretrained EfficientNet as backbone architecture for breast tumor cell nuclei segmentation and uses the multi-organ transfer learning approach to segment nuclei of breast tumor cells. We attempt to experiment and evaluate the performance of the network on the MonuSeg training dataset and Triple Negative Breast Cancer (TNBC) testing dataset, both are Hematoxylin and Eosin (H & E)-stained images. The results have shown that EfficientUnet++ architecture and the multi-organ transfer learning approach had outperformed other techniques and produced notable accuracy for breast tumor cell nuclei segmentation.

• Asian Pacific Journal of Cancer Prevention
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• 제15권24호
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• pp.10573-10576
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• 2015

Background: Accuracy in feature extraction is an important factor in image classification and retrieval. In this paper, a breast tissue density classification and image retrieval model is introduced for breast cancer detection based on thermographic images. The new method of thermographic image analysis for automated detection of high tumor risk areas, based on two-directional two-dimensional principal component analysis technique for feature extraction, and a support vector machine for thermographic image retrieval was tested on 400 images. The sensitivity and specificity of the model are 100% and 98%, respectively.