• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.1015-1026
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• 2019

Objective: The objective of this study was to evaluate three different degrees of white striping (WS) addressing their automatic assessment and customer acceptance. The WS classification was performed based on a computer vision system (CVS), exploring different machine learning (ML) algorithms and the most important image features. Moreover, it was verified by consumer acceptance and purchase intent. Methods: The samples for image analysis were classified by trained specialists, according to severity degrees regarding visual and firmness aspects. Samples were obtained with a digital camera, and 25 features were extracted from these images. ML algorithms were applied aiming to induce a model capable of classifying the samples into three severity degrees. In addition, two sensory analyses were performed: 75 samples properly grilled were used for the first sensory test, and 9 photos for the second. All tests were performed using a 10-cm hybrid hedonic scale (acceptance test) and a 5-point scale (purchase intention). Results: The information gain metric ranked 13 attributes. However, just one type of image feature was not enough to describe the phenomenon. The classification models support vector machine, fuzzy-W, and random forest showed the best results with similar general accuracy (86.4%). The worst performance was obtained by multilayer perceptron (70.9%) with the high error rate in normal (NORM) sample predictions. The sensory analysis of acceptance verified that WS myopathy negatively affects the texture of the broiler breast fillets when grilled and the appearance attribute of the raw samples, which influenced the purchase intention scores of raw samples. Conclusion: The proposed system has proved to be adequate (fast and accurate) for the classification of WS samples. The sensory analysis of acceptance showed that WS myopathy negatively affects the tenderness of the broiler breast fillets when grilled, while the appearance attribute of the raw samples eventually influenced purchase intentions.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.919-927
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• 2023

Elastography utilizes the fact that the tissue of a malignant tumor is harder than that of a benign tumor and increases the specificity of diagnosis according to the elastic modulus of the tumor, helping to reduce unnecessary biopsies. However, the reliability of elastography can be influenced by the equipment used and the examiner's skills. In this study, the researchers analyzed the reproducibility of elastography by evaluating phantom images when measuring the elasticity values repeatedly. Phantoms were created using silicone and gelatin with different levels of stiffness, and they were inserted at varying depths from the surface. The elasticity values were measured using shear wave elastography. The study aimed to determine whether the reproducibility of elasticity values remains consistent depending on the stiffness and depth of the lesions. The experimental results showed that there was no statistically significant correlation between the elasticity values obtained through shear wave elastography and the depth or stiffness of the lesions. However, in the lesions with the lowest stiffness, the elasticity values were statistically significant (p<0.001) and showed a high correlation with the depth of the lesions. Although there were variations in the measured elasticity values based on the differences in lesion stiffness and depth, these differences did not significantly impact the diagnosis. Therefore, shear wave elastography remains a reliable diagnostic method, and it is suggested that it can be helpful in the diagnosis of breast lesions.

• Korean Journal of Radiology
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• v.25 no.6
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• pp.511-517
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• 2024

Objective: To prospectively investigate the influence of the menstrual cycle on the background parenchymal signal (BPS) and apparent diffusion coefficient (ADC) of the breast on diffusion-weighted MRI (DW-MRI) in healthy premenopausal women. Materials and Methods: Seven healthy premenopausal women (median age, 37 years; range, 33-49 years) with regular menstrual cycles participated in this study. DW-MRI was performed during each of the four phases of the menstrual cycle (four examinations in total). Three radiologists independently assessed the BPS visual grade on images with b-values of 800 sec/mm² (b800), 1200 sec/mm² (b1200), and a synthetic 1500 sec/mm² (sb1500). Additionally, one radiologist conducted a quantitative analysis to measure the BPS volume (%) and ADC values of the BPS (ADC_BPS) and fibroglandular tissue (ADC_FGT). Changes in the visual grade, BPS volume (%), ADC_BPS, and ADC_FGT during the menstrual cycle were descriptively analyzed. Results: The visual grade of BPS in seven women varied from mild to marked on b800 and from minimal to moderate on b1200 and sb1500. As the b-value increased, the visual grade of BPS decreased. On b800 and sb1500, two of the seven volunteers showed the highest visual grade in the early follicular phase (EFP). On b1200, three of the seven volunteers showed the highest visual grades in EFP. The BPS volume (%) on b800 and b1200 showed the highest value in three of the six volunteers with dense breasts in EFP. Three of the seven volunteers showed the lowest ADC_BPS in the EFP. Four of the seven volunteers showed the highest ADC_BPS in the early luteal phase (ELP) and the lowest ADC_FGT in the late follicular phase (LFP). Conclusion: Most volunteers did not exhibit specific BPS patterns during their menstrual cycles. However, the highest BPS and lowest ADC_BPS were more frequently observed in EFP than in the other menstrual cycle phases, whereas the highest ADC_BPS was more common in ELP. The lowest ADC_FGT was more frequent in LFP.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.67-74
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• 2016

Drone images with high spatial resolution are emerging as an alternative to previous studies with extraction limits in high density forests. Individual tree in the dense forests were extracted from drone images. To detect the individual tree extracted through the image segmentation process, the image segmentation results were compared between the combination of DSM and all R,G,B band and the combination of DSM and R,G,B band separately. The changes in the tree density of a deciduous forest was experimented by time and image. Especially the image of May when the forests are dense, among the images of March, April, May, the individual tree extraction rate based on the trees surveyed on the site was 50%. The analysis results of the width of crown showed that the RMSE was less than 1.5m, which was the best result. For extraction of the experimental area, the two sizes of medium and small trees were extracted, and the extraction accuracy of the small trees was higher. The forest tree volume and forest biomass could be estimated if the tree height is extracted based on the above data and the DBH(diameter at breast height) is estimated using the relational expression between crown width and DBH.

• Journal of Biomedical Engineering Research
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• v.38 no.6
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• pp.321-329
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• 2017

This paper presents a bone metastasis Detection algorithm on abdominal computed tomography images for early detection using fully convolutional neural networks. The images were taken from patients with various cancers (such as lung cancer, breast cancer, colorectal cancer, etc), and thus the locations of those lesions were varied. To overcome the lack of data, we augmented the data by adjusting the brightness of the images or flipping the images. Before the augmentation, when 70% of the whole data were used in the pre-test, we could obtain the pixel-wise sensitivity of 18.75%, the specificity of 99.97% on the average of test dataset. With the augmentation, we could obtain the sensitivity of 30.65%, the specificity of 99.96%. The increase in sensitivity shows that the augmentation was effective. In the result obtained by using the whole data, the sensitivity of 38.62%, the specificity of 99.94% and the accuracy of 99.81% in the pixel-wise. lesion-wise sensitivity is 88.89% while the false alarm per case is 0.5. The results of this study did not reach the level that could substitute for the clinician. However, it may be helpful for radiologists when it can be used as a screening tool.

• Journal of Biomedical Engineering Research
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• v.33 no.4
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• pp.213-222
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• 2012

While much has been learned about the mechanisms of metastatic spread of cancer to bone, there has been little headway in establishing guidelines for monitoring the alteration in bone quality and estimating fracture risk. The aims of this study are, therefore, 1) to evaluate bone quality induced by metastatic bone tumor by analyzing the characteristics on bone microarchitecture and degree of bone mineralization and 2) analyze fracture risk increased secondary to the bone quality changes by metastatic bone tumor through calculating mechanical rigidities based on in-vivo micro CT images. For this study, eighteen female SD rats (12 weeks old, approximate 250 g) were randomly allocated in Sham and Tumor groups. W256 (Walker carcinosarcoma 256 malignant breast cancer cell) was inoculated in the right femur (intraosseous injection) in Tumor group, while 0.9% NaCl (saline solution) was injected in Sham group. The right hind limbs of all rats were scanned by in-vivo micro-CT to acquire structural parameters and degree of bone mineralization at 0 week, 4 weeks, 8 weeks, and 12 weeks after surgery. At the same time, urine was collected by metabolic cages for a biochemical marker test in order to evaluate bone resorption. Then, bone metastasis had been directly identified by positron emission tomography. Finally, axial, bending and torsional rigidities had been calculated based on in-vivo micro CT images for predict fracture risk. The results of this study showed that metastatic bone tumor might induce significant decrease in bone quality and increase of fracture risk. This study may be helpful to monitoring a degree of bone metastasis and predicting fracture risk due to metastatic bone tumor. In addition, this noninvasive diagnostic methodology may be utilized for evaluating other bone metabolic diseases such as osteoporosis.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.4
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• pp.20-28
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• 2008

We propose a radial image processing method in a discrete polar coordinate system based on L1-norm. For this purpose, we first verified that the polar coordinate based on L2-norm can not exist in discrete system and then develop a method converting the Cartesian coordinate to the discrete polar coordinate. We apply the proposed method to smooth mass images of breast tissue and to detect the boundaries of extremely deformable objects. Compared to the Gaussian smoothing method performed in the Cartesian coordinate system, the proposed method stabilized the image signal while maintaining the overall radial shape of mass images. The proposed boundary detection method can detect shapes with high precision while conventional edge detectors can not accurately detect the shape of deformable objects. We also exploit the method to perform pupil detection and have had good experimental results.

• Journal of the Korean Society of Physical Medicine
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• v.16 no.2
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• pp.45-52
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• 2021

PURPOSE: This study examined the imaging procedure of pectoralis minor muscle thickness and assessed the intra- and inter-rater reliability of the muscle thickness measured by two raters using rehabilitative ultrasound imaging (RUSI) in healthy individuals. METHODS: Fifteen participants (aged 21 - 28, seven females, and eight males) were involved in the study. The primary rater palpated the coracoid process and the fourth rib, defined as the width of the index finger lateral to the sternum to avoid breast tissues, and lined the two landmarks. The second examiner checked 1 / 3 (1st point) and 1 / 2 (2nd point) of the line length as measurement points. The two raters obtained right side muscle images of the participants at a standardized sitting position using RUSI with a 7.5 MHz linear transducer at 40mm depth. For intra-rater reliability, the principal rater took three images per point and tried to take one more with an interval. For the inter-rater reliability, the other rater performed the same tasks as the principal rater on the same day. The reliability was analyzed using the intra-class correlation coefficient (ICC), the standard error of the measurement (SEM), and Bland and Altman plots. RESULTS: The reliability at all points was excellent for the same rater (ICC_3,1 = .973 - .978, SEM = .042 - .046), and between raters (ICC_2,1 = .939 - .959, SEM = .059 - .097). CONCLUSION: These findings show that the RUSI could be reliable for examining the pectoralis minor muscle thickness in healthy individuals at all measurement sites.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.2
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• pp.337-343
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• 2014

Purpose : The aim of this study is to evaluate unwanted scattered dose to ovary by scattering and leakage generated from treatment fields of Tomotherapy for childbearing woman with breast cancer. Materials and Methods : The radiation treatments plans for left breast cancer were established using Tomotherapy planning system (Tomotherapy, Inc, USA). They were generated by using helical and direct Tomotherapy methods for comparison. The CT images for the planning were scanned with 2.5 mm slice thickness using anthropomorphic phantom (Alderson-Rando phantom, The Phantom Laboratory, USA). The measurement points for the ovary dose were determined at the points laterally 30 cm apart from mid-point of treatment field of the pelvis. The measurements were repeated five times and averaged using glass dosimeters (1.5 mm diameter and 12 mm of length) equipped with low-energy correction filter. The measures dose values were also converted to Organ Equivalent Dose (OED) by the linear exponential dose-response model. Results : Scattered doses of ovary which were measured based on two methods of Tomo helical and Tomo direct showed average of $64.94{\pm}0.84mGy$ and $37.64{\pm}1.20mGy$ in left ovary part and average of $64.38{\pm}1.85mGy$ and $32.96{\pm}1.11mGy$ in right ovary part. This showed when executing Tomotherapy, measured scattered dose of Tomo Helical method which has relatively greater monitor units (MUs) and longer irradiation time are approximately 1.8 times higher than Tomo direct method. Conclusion : Scattered dose of left and right ovary of childbearing women is lower than ICRP recommended does which is not seriously worried level against the infertility and secondary cancer occurrence. However, as breast cancer occurrence ages become younger in the future and radiation therapy using high-precision image guidance equipment like Tomotherapy is developed, clinical follow-up studies about the ovary dose of childbearing women patients would be more required.

• Investigative Magnetic Resonance Imaging
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• v.18 no.1
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• pp.1-6
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• 2014

Purpose : $T_2{^*}$ relaxation time which includes susceptibility information represents unique feature of tissue. The objective of this study was to investigate $T_2{^*}$ relaxation times of the normal glandular tissue and fat of breast using a 3T MRI system. Materials and Methods: Seven-echo MR Images were acquired from 52 female subjects (age $49{\pm}12 $years; range, 25 to 75) using a three-dimensional (3D) gradient-echo sequence. Echo times were between 2.28 ms to 25.72 ms in 3.91 ms steps. Voxel-based $T_2{^*}$ relaxation times and $R_2{^*}$ relaxation rate maps were calculated by using the linear curve fitting for each subject. The 3D regions-of-interest (ROI) of the normal glandular tissue and fat were drawn on the longest echo-time image to obtain $T_2{^*}$ and $R_2{^*}$ values. Mean values of those parameters were calculated over all subjects. Results: The 3D ROI sizes were $4818{\pm}4679$ voxels and $1455{\pm}785$ voxels for the normal glandular tissue and fat, respectively. The mean $T_2{^*}$ values were $22.40{\pm}5.61ms$ and $36.36{\pm}8.77ms$ for normal glandular tissue and fat, respectively. The mean $R_2{^*}$ values were $0.0524{\pm}0.0134/ms$ and $0.0297{\pm}0.0069/ms$ for the normal glandular tissue and fat, respectively. Conclusion: $T_2{^*}$ and $R_2{^*}$ values were measured from human breast tissues. $T_2{^*}$ of the normal glandular tissue was shorter than that of fat. Measurement of $T_2{^*}$ relaxation time could be important to understand susceptibility effects in the breast cancer and the normal tissue.