• Journal of Radiopharmaceuticals and Molecular Probes
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• v.1 no.1
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• pp.62-73
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• 2015

We developed an evans blue-indocyanine green-$^{99m}Tc$-human serum albumin conjugate for sentinel lymph node mapping and we describe its unique potential usage for clinical implications. This conjugate has combined the strengths of visible blue dye, near-infrared fluorescence and radioisotope into one single conjugate without any additional weakness/disadvantage. All the components of evans blue-indocyanine green-$^{99m}Tc$-human serum albumin are safe and of low cost, and they have already been clinically used. This conjugate was stable in the serum, it showed a long retention time in the lymphatic system and the lymph nodes showed a much higher signal-to-noise ratio after the conjugate was injected intradermally into the paw of mice. Both the single-photon emission computed tomography and near-infrared fluorescent images of the mice were successfully obtained at the same time as the excised sentinel lymph nodes showed blue color. The visual color, near-infrared fluorescence and gamma ray from this agent could be complementary for each other in all the steps of sentinel lymph node sampling: exploring and planning sentinel lymph node before excision with visualization of the exact sentinel lymph node location during an operation. Therefore, the triple modal agent will possibly be very ideal for sentinel lymph node mapping because of the high signal-to-noise ratio for non-invasive imaging and its complementary multimodal nature, easy preparation and safety. It is promising for clinical applications and it may have great advantages over the traditional single modal methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.1
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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.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.103-109
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• 2022

To maintain improved image quality in mammography, the quality control process is performed using the ACR (American college of radiology) phantom. In addition, many studied were performed by fabricating the customized breast phantom to provide more information in mammography. Thus, the purpose of this study was to evaluate the image quality by designing the modified ACR phantoms. The five modified acrlylic ACR phantoms were designed by considering insert position and phantom thickness. The phantoms were consisted of 4.5, 3.0, and 1.5 cm in terms of phantom thickness, and 3.0, 2.0, and 0.5 cm in terms of insert position, respectively. The acquired images were evaluated by PSNR (peak signal to noise ratio), RMSE (root mean square error), CC (correlation coefficient), CNR (contrast to noise ratio), and COV (coefficient of variation). Based on the similarity analysis, the result is suitable between conventional and new designed phantoms. In addition, the CNR and COV results in terms of insert position showed that image quality for 0.5 cm was 2.3 and 27.4% improved compared with 2 and 3 cm, respectively. According to phantom thickness results, the CNR result for 1.5 cm and COV result for 4.5 cm were 50.1 and 62.7% improved compared with that those conditions. In conclusion, we confirmed that the image quality depends on the breast size and thickness through modified ACR phantom study.

• Journal of Radiation Industry
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• v.17 no.4
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• pp.391-396
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• 2023

Currently, state-of-the-art devices such as SPECT, PET/CT, and PET/MRI are rapidly spreading nationwide, and the penetration rate of nuclear medical devices is also ranked fifth in the world. However, PET/MRI's system is slower and less common because it is more complex than PET/CT. The purpose of this study is to provide optimal information on PET/MRI according to the patient's disease. The subjects obtained information on head and neck cancer, pediatric patients, breast cancer patients, heart disease patients, lung cancer patients, and rectal cancer patients. We tried to accumulate protocols by obtaining a lot of information about each disease. In diagnosing head and neck cancer, it is believed that it is highly likely to be used in evaluating preoperative stage determination, recurrence and remote metastasis after treatment, and unclear primary cervical lymph node metastasis. Diagnosis and continuous follow-up of pediatric patients can increase patient benefits by minimizing radiation exposure. Breast cancer provides a comprehensive evaluation of the clinical need to determine the extent of disease in breast and local lymph nodes and the systematic stages of early diagnosis or recurrence. In diagnosing heart disease patients, MR-based PET motion correction helps to realize the full potential of PET images. For lung cancer patients, the clinical value and usefulness of the resolution and detection ability of integrated PET/MRI for soft tissues such as lung cancer will be sufficient. In diagnosing rectal cancer patients, the detection of missing residual diseases can change the clinical response evaluation for rectal cancer patients treated with TNT, and both the initial stage and treatment response evaluation are possible. Therefore, this literature study provided basic clinical data for PET/MRI tests.

• Investigative Magnetic Resonance Imaging
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• v.14 no.1
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• pp.41-46
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• 2010

Purpose : To evaluate the role of magnetic resonance imaging (MRI) in the diagnosis of papillary lesions of the breast. Materials and methods : Among 45 papillary lesions diagnosed at ultrasonography-guided core biopsy (USCB), 27 benign papillary lesions in 22 patients who underwent breast MRI were reviewed. The excsional biopsy was performed in 1-10 days after MRI was done. In MRI findings, lesions were considered suspicious if they show irregular, rim enhancement, or linear enhancement in morphologic evaluation, or washout enhancement pattern of delayed phase in dynamic enhancement characteristics. Diffusionweighted images were analyzed according to visibility of lesions. MRI findings were correlated with pathologic results at excisional biopsy. Results : At excisional biopsy, two lesions (9%) were diagnosed malignant in 22 benign papillary lesions without atypia by USCB and 4 (80%) were malignant in 5 benign papillary lesions with atypia by USCB. Among 18 lesions detected on MRI, 16 lesions showed suspicious findings on MRI, 11 lesions (69%) were diagnosed as benign and 5 (31%) were malignant. Among 12 lesions detected on diffusion weighted imaging, 10 lesions were diagnosed as benign and 2 were malignant. MRI findings were not significantly correlated with pathologic results at excisional biopsy. Conclusion : MRI findings were not useful to predict malignancy in benign papillary lesions diagnosed at USCB, because MRI findings of these were mostly suspicious (88.9%, 16/18). The benign papillary lesion should be included in the false positive lesion on breast MRI.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3C
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• pp.374-386
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• 2004

The mammogram provides the way to observe detailed internal organization of breasts to radiologists for the early detection. This paper is mainly focused on efficiently detecting the Microcalcification's Region Of Interest(ROI)s. Breast cancers can be caused from either microcalcifications or masses. Microcalcifications are appeared in a digital mammogram as tiny dots that have a little higher gray levels than their surrounding pixels. We can roughly determine the area which possibly contain microcalifications. In general, it is very challenging to find all the microcalcifications in a digital mammogram, because they are similar to some tissue parts of a breast. To efficiently detect microcalcifications ROI, we used four sequential processes; preprocessing for breast area detection, modified multilevel thresholding, ROI selection using simple thresholding filters and final ROI selection with two stages of neural networks. The filtering process with boundary conditions removes easily-distinguishable tissues while keeping all microcalcifications so that it cleans the thresholded mammogram images and speeds up the later processing by the average of 86％. The first neural network shows the average of 96.66％ recognition rate. The second neural network performs better by showing the average recognition rate 98.26％. By removing all tissues while keeping microcalcifications as much as possible, the next parts of a CAD system for detecting breast cancers can become much simpler.

• The Journal of Korean Society for Radiation Therapy
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• v.33
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• pp.55-62
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• 2021

Purpose: This study aims to contribute to the reduction of complications of breast cancer radiation therapy by analyzing skin dose differences due to Set-up error. Materials and Method: Pseudo breast was produced using a 3D printer, applied to the phantom, and images were acquired through CT. Treatment plan was carried out that the PTV, which contains 95% of the prescription dose, could be more than 95% of the volume, so that Dmax did not exceed 107% of the prescription dose. The Set-up error was evaluated by applying ±1mm/±3mm/±5mm to the X-axis, Y-axis, and Z-axis. Results: The dose-variation in skin due to Set-up error was approximately 106% to 123% compared to prescription dose, and the highest dose in skin was 49.24 Gy at 5mm Set-up error in the lateral direction of the X-axis. More than 107% of the prescription dose was the widest at 6.87 cc in skin lateral. Conclusions: If a Set-up error occurs during left breast cancer VMAT, a great difference in skin dose was shown in the lateral direction of the X-axis. If more effort is made to align the X-axis of the breast treated during CBCT registration, the dose-variation of skin will be reduced.

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.492-497
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• 2004

Purpose: it is very important to differentiate breast cancer from benign mass. There are many reports to evaluate the differential diagnosis under the several diagnostic tools. We evaluated the usefulness of mammography and Tc-99m MIBI scintimammography in the differential diagnosis of breast mass and correlated with pathologic findings. Materials and Methods: This study included 80 patients (a8e: 24-72, mean: 48.4) who underwent mammography and Tc-99m MIBI scintimammography for breast masses. Scintimammographies (anterior-posterior and lateral projections) were acquired in 10 minutes and 2 hours after intravenous injection of Tc-99m MIBI. four specialists in diagnostic radioloay and nuclear medicine evaluated the findings of breast masses under the mammography and Tc-99m MIBI scintimammography, and calculated the tumor to background (T/B) ratio. The pathologic results were obtained and we statistically analyzed the correlations between pathologic results and imaging findings under the mammography and Tc-99m MIBI scintimammography by chi-square and correlation test. Results: The sensitivity, specificity, positive predictive value, and negative predictive value of mammography for detection of breast cancer were 87.5%, 56.3%, 75.0%), and 75.0% respectively. 45 cases of 80 patients were suspicious for breast cancer under the Tc-99m MIBI scintimammography. 41 cases of 45 patients were confirmed as breast cancer and the remaining 4 cases were confirmed as benign masses. The sensitivity, specificity, positive predictive value and negative predictive value of Tc-99m MIBI scintimammography for detection of breast cancer were 85.4%, 87.5%, 91.1%, and 80.8% respectively. The sensitivity of scintimammography was lower than that of mammography for detection of breast cancer, however the specificity, positive predictive value, and negative predictive value were higher. In the benign mass, the mean T/B ratio in 10 minutes was $1.409{\pm}0.30$, and that in 2 hours was $1.267{\pm}0.42$. The maximal T/B ratio of benign mass in 10 minutes was $1.604{\pm}0.42$, and that in 2 hours was $1.476{\pm}0.50$. In the malignant mass, the mean T/B ratio in 10 minutes was $2.220{\pm}1.07$, and that in 2 hours was $1.842{\pm}0.75$. The maximal T/B ratio of malignant mass was $2.993{\pm}1.94$, and that in 2 hours was $2.480{\pm}1.34$. And the T/B ratio under the early and delayed images were meaningful. Conclusion: The scintimammography is useful diagnostic tool to differentiate breast cancer from benign mass, although the sensitivity of mammography for detection of breast mass is high. Especially, the use of the T/B ratio is helpful to diagnose breast cancer.

• Progress in Medical Physics
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• v.30 no.2
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• pp.49-58
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• 2019

Purpose: Automated analytical systems have begun to emerge as a database system that enables the scanning of medical images to be performed on computers and the construction of big data. Deep-learning artificial intelligence (AI) architectures have been developed and applied to medical images, making high-precision diagnosis possible. Materials and Methods: For diagnosis, the medical images need to be labeled and standardized. After pre-processing the data and entering them into the deep-learning architecture, the final diagnosis results can be obtained quickly and accurately. To solve the problem of overfitting because of an insufficient amount of labeled data, data augmentation is performed through rotation, using left and right flips to artificially increase the amount of data. Because various deep-learning architectures have been developed and publicized over the past few years, the results of the diagnosis can be obtained by entering a medical image. Results: Classification and regression are performed by a supervised machine-learning method and clustering and generation are performed by an unsupervised machine-learning method. When the convolutional neural network (CNN) method is applied to the deep-learning layer, feature extraction can be used to classify diseases very efficiently and thus to diagnose various diseases. Conclusions: AI, using a deep-learning architecture, has expertise in medical image analysis of the nerves, retina, lungs, digital pathology, breast, heart, abdomen, and musculo-skeletal system.

• Radiation Oncology Journal
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• v.20 no.1
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• pp.24-33
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• 2002

Purpose : In order to improve dose homogeneity and to reduce acute toxicity in tangential whole breast radiotherapy, we evaluated two treatment techniques using multiple static fields or universal compensators. Materials and Methods : 1) Multistatic field technique : Using a three dimensional radiation treatment planning system, Adac Pinnacle 4.0, we accomplished a conventional wedged tangential plan. Examining the isodose distributions, a third field which blocked overdose regions was designed and an opposing field was created by using an automatic function of RTPS. Weighting of the beams was tuned until an ideal dose distribution was obtained. Another pair of beams were added when the dose homogeneity was not satisfactory. 2) Universal compensator technique : The breast shapes and sizes were obtained from the CT images of 20 patients who received whole breast radiation therapy at our institution. The data obtained were averaged and a pair of universal physical compensators were designed for the averaged data. DII (Dose Inhomogeneity Index : percentage volume of PTV outside $95\~105\%$ of the prescribed dose) $D_{max}$ (the maximum point dose in the PTV) and isodose distributions for each technique were compared. Results : The multistatic field technique was found to be superior to the conventional technique, reducing the mean value of DII by $14.6\%$ (p value<0.000) and the $D_{max}$ by $4.7\%$ (p value<0.000). The universal compensator was not significantly superior to the conventional technique since it decreased $D_{max}$ by $0.3\%$ (p value=0.867) and reduced DII by $3.7\%$ (p value=0.260). However, it decreased the value of DII by maximum $18\%$ when patients' breast shapes fitted in with the compensator geometry. Conclusion : The multistatic field technique is effective for improving dose homogeneity for whole breast radiation therapy and is applicable to all patients, whereas the use of universal compensators is effective only in patients whose breast shapes fit inwith the universal compensator geometry, and thus has limited applicability.