• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.15 no.3
• /
• pp.180-185
• /
• 2015

Digital infrared thermal imaging is a non-invasive adjunctive diagnostic technique that allows an examiner to visualize and quantify changes in skin surface temperature. The asymmetry of temperature differences between the diseased and the contralateral healthy body parts can be automatically analyzed and has been studied in many areas of medical science. In this paper, we propose a method for intelligent automatic asymmetry detection based on a K-means analysis and a YCbCr color model. The implemented software successfully visualizes an asymmetric distribution of colors with respect to the patients’ health status.

• Imaging Science in Dentistry
• /
• v.49 no.3
• /
• pp.219-228
• /
• 2019

Purpose: The aim of this study was to determine the reasons and solutions for intraoral phosphor storage plate (PSP) image artifacts and errors, and to develop an appropriate classification of the artifacts. Materials and Methods: This study involved the retrospective examination of 5,000 intraoral images that had been obtained using a phosphor plate system. Image artifacts were examined on the radiographs and classified according to possible causative factors. Results: Artifacts were observed in 1,822 of the 5,000 images. After examination of the images, the errors were divided into 6 groups based on their causes, as follows: images with operator errors, superposition of undesirable structures, ambient light errors, plate artifacts (physical deformations and contamination), scanner artifacts, and software artifacts. The groups were then re-examined and divided into 45 subheadings. Conclusion: Identification of image artifacts can help to improve the quality of the radiographic image and control the radiation dose. Knowledge of the basic physics and technology of PSP systems could aid to reduce the need for repeated radiography.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.12
• /
• pp.131-136
• /
• 2018

This paper proposes a computer-aided diagnostic algorithm in a non-invasive way. Currently, clinical diagnosis of jaundice is performed through blood sampling. Unlike the old methods, the non-invasive method will enable parents to measure newborns' jaundice by only using their mobile phones. The proposed algorithm enables high accuracy and quick diagnosis through machine learning. In here, we used the SVM model of machine learning that learned the feature extracted through image preprocessing and we used the international jaundice research data as the test data set. As a result of applying our developed algorithm, it took about 5 seconds to diagnose jaundice and it showed a 93.4% prediction accuracy. The software is real-time diagnosed and it minimizes the infant's pain by non-invasive method and parents can easily and temporarily diagnose newborns' jaundice. In the future, we aim to use the jaundice photograph of the newborn babies' data as our test data set for more accurate results.

• Nuclear Medicine and Molecular Imaging
• /
• v.41 no.3
• /
• pp.201-208
• /
• 2007

Purpose: We investigated whether the diagnostic performance of SPECT scintimammography (SMM) can be improved by adding computer-aided diagnosis (CAD) of ultrasonography (US). Materials and methods: We reviewed breast SPECT SMM images and corresponding US images from 40 patients with breast masses (21 malignant and 19 benign tumors). The quantitative data of SPECT SMM were obtained as the uptake ratio of lesion to contralateral normal breast. The morphologic features of the breast lesions on US were extracted and quantitated using the automated CAD software program. The diagnostic performance of SPECT SMM and CAD of US alone was determined using receiver operating characteristic (ROC) curve analysis. The best discriminating parameter (D-value) combining SPECT SMM and the CAD of US was created. The sensitivity, specificity and accuracy of combined two diagnostic modalities were compared to those of a single one. Results: Both SPECT SMM and CAD of US showed a relatively good diagnostic performance (area under curve = 0.846 and 0.831, respectively). Combining the results of SPECT SMM and CAD of US resulted in improved diagnostic performance (area under curve =0.860), but there was no statistical differerence in sensitivity, specificity and accuracy between the combined method and a single modality. Conclusion: It seems that combining the results of SPECT SMM and CAD of breast US do not significantly improve the diagnostic performance for diagnosis of breast cancer, compared with that of SPECT SMM alone. However, SPECT SMM and CAD of US may complement each other in differential diagnosis of breast cancer.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.8
• /
• pp.4785-4790
• /
• 2013

Background and Objectives: Evidence for associations between alcohol consumption with breast cancer survival are conflicting, so we conducted the present meta-analysis. Methods: Comprehensive searches were conducted to find cohort studies that evaluated the relationship between alcohol consumption with breast cancer survival. Data were analyzed with meta-analysis software. Results: We included 25 cohort studies. The meta-analysis results showed that alcohol consumption was not associated with increased breast cancer mortality and recurrence after pooling all data from highest versus lowest comparisons. Subgroup analyses showed that pre-diagnostic or post-diagnostic consumpotion, and ER status did not affect the relationship with breast cancer mortality and recurrence. Although the relationships of different alcohol consumption with breast cancer mortality and recurrence were not significant, there seemed to be a dose-response relationship of alcohol consumption with breast cancer mortality and recurrence. Only alcohol consumption of >20 g/d was associated with increased breast cancer mortality, but not with increased breast cancer recurrence. Conclusion: Although our meta-analysis showed alcohol drinking was not associated with increased breast cancer mortality and recurrence, there seemed to be a dose-response relationship of alcohol consumption with breast cancer mortality and recurrence and alcohol consumption of >20 g/d was associated with increased breast cancer mortality.

• Imaging Science in Dentistry
• /
• v.43 no.4
• /
• pp.289-293
• /
• 2013

Purpose: This study was performed to determine the relationship between the stage of tooth eruption (both vertical and mesio-angular) and chronological age. Materials and Methods: Indirect digital panoramic radiographs were used to measure the distances from the dentinoenamel junction (DEJ) of the second molars to the occlusal plane of the second molar teeth and of the adjacent third molars in 264 Thai males and 437 Thai females using ImageJ software. The ratio of those distances was calculated by patient age, and the correlation coefficient of the ratio of the third molar length to the second molar length was calculated. Results: The correlation between the height of the vertically erupted upper third molar teeth and age was at the intermediate level. The age range of ${\geq}15$ to <16 years was noted to be the range in which the correlation between the chronological age determined from the eruptional height and actual chronological age was statistically significant. The mean age of the female subjects, in which the position of the right upper third molar teeth was at or above the DEJ of the adjacent second molar but below one half of its coronal height was $19.9{\pm}2.6$ years. That for the left side was $20.2{\pm}2.7$ years. The mean ages of the male subjects were $20.1{\pm}3.3$ years and $19.8{\pm}2.7$ years for the right and left sides, respectively. Conclusion: It might be possible to predict chronological age from the eruption height of the wisdom teeth.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.8
• /
• pp.47-54
• /
• 2020

Developmental disorders are impairments of brain and/or central nervous system and refer to a disorder of brain function that affects languages, communication skills, perception, sociality and so on. In diagnosis of developmental disorders, behavioral response such as expressing emotions in proper situation is one of observable indicators that tells whether or not individual has the disorders. However, diagnosis by observation can allow subjective evaluation that leads erroneous conclusion. This research presents the technological environment and data acquisition system for AI based screening of autism disorder. The environment was built considering activities for two screening protocols, namely Autism Diagnostic Observation Schedule (ADOS) and Behavior Development Screening for Toddler (BeDevel). The activities between therapist and baby during the screening are fully recorded. The proposed software in this research was designed to support recording, monitoring and data tagging for learning AI algorithms.

• The Journal of Korean Academy of Prosthodontics
• /
• v.39 no.3
• /
• pp.273-281
• /
• 2001

Digital subtraction radiography may be one of the most precise and noninvasive methods for assessing subtle density changes in peri-implant bone, providing additional diagnostic information on implant tissue integration in overall maintenance. The aims of this study were to evaluate density changes after first, second surgery of dental implant and to measure the amount of marginal bone loss 9 months after second surgery using digital subtraction radiography. Bone change around 30 screw-shaped implants in 16 patients were assessed on radiographs. 17 Branemark implants of 3.75mm in diameter(Nobel Biocare, Goteborg, Sweden), 2 Branemark implants of 5.0mm in diameter, 11 $Replace^{TM}$ implants of 4.3mm in diameter(Nobel Biocare, Goteborg, Sweden) were used. To standardize the projection geometry of serial radiographs of implants, customized bite block was fabricated using XCP film holder(Rinn Corporation, Elgin, IL.) with polyether impression material of Impregum(ESPE, Germany) and direct digital image was obtained. Qualitative and quantitative changes on radiographs were measured with Emago software(The Oral Diagnostic System, Amsterdam, Netherlands). The results were as follows: 1. The peri-implant bone density of 69.2% implants did not change and the peri-implant bone density of 30.8% implants decreased after 3 months following first surgery. 2. The crestal bone density of 53.9% implants decreased first 3 months after second surgery. The crestal bone density of 58.8% implants increased 9 months after second surgery. No density change was observed around the midportion of the implants after second surgery, 3. The amount of marginal bone loss between different kinds of implants showed no statistically significant differences (p>0.05). 4. More than 90% of total marginal bone loss recorded in a 9-month period occurred during the first 3 months.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2008.03a
• /
• pp.16-21
• /
• 2008

Aero-engine, as one kind of rotating machinery with complex structure and high rotating speed, has complicated vibration faults. Therefore, condition monitoring and fault diagnosis system is very important for airplane security. In this paper, a vibration data acquisition and intelligent fault diagnosis system is introduced. First, the vibration data acquisition part is described in detail. This part consists of hardware acquisition modules and software analysis modules which can realize real-time data acquisition and analysis, off-line data analysis, trend analysis, fault simulation and graphical result display. The acquisition vibration data are prepared for the following intelligent fault diagnosis. Secondly, two advanced artificial intelligent(AI) methods, mapping-based and rule-based, are discussed. One is artificial neural network(ANN) which is an ideal tool for aero-engine fault diagnosis and has strong ability to learn complex nonlinear functions. The other is data mining, another AI method, has advantages of discovering knowledge from massive data and automatically extracting diagnostic rules. Thirdly, lots of historical data are used for training the ANN and extracting rules by data mining. Then, real-time data are input into the trained ANN for mapping-based fault diagnosis. At the same time, extracted rules are revised by expert experience and used for rule-based fault diagnosis. From the results of the experiments, the conclusion is obvious that both the two AI methods are effective on aero-engine vibration fault diagnosis, while each of them has its individual quality. The whole system can be developed in local vibration monitoring and real-time fault diagnosis for aero-engine.

• Journal of Internet Computing and Services
• /
• v.25 no.3
• /
• pp.19-25
• /
• 2024

The worldwide aging population trend is causing an increase in the incidence of major retinal diseases that can lead to blindness, including glaucoma, cataract, and macular degeneration. In the field of ophthalmology, there is a focused interest in diagnosing diseases that are difficult to prevent in order to reduce the rate of blindness. This study proposes a deep learning approach to accurately diagnose ocular diseases in fundus photographs using less data than traditional methods. For this, Convolutional Neural Network (CNN) models capable of effective learning with limited data were selected to classify Conventional Fundus Images (CFI) from various ocular disease patients. The chosen CNN models demonstrated exceptional performance, achieving high Accuracy, Precision, Recall, and F1-score values. This approach reduces manual analysis by ophthalmologists, shortens consultation times, and provides consistent diagnostic results, making it an efficient and accurate diagnostic tool in the medical field.