• 시스템엔지니어링학술지
• /
• 제17권2호
• /
• pp.91-97
• /
• 2021

User interface for cancer classification system is a software application with clinician's friendly tools and functions to diagnose cancer from pathology images. Pathology evolved from manual diagnosis to computer-aided diagnosis with the help of Artificial Intelligence tools and algorithms. In this paper, we explained each block of the project life cycle for the implementation of automated breast cancer classification software using AI and machine learning algorithms to classify normal and invasive breast histology images. The system was designed to help the pathologists in an automatic and efficient diagnosis of breast cancer. To design the classification model, Hematoxylin and Eosin (H&E) stained breast histology images were obtained from the ICIAR Breast Cancer challenge. These images are stain normalized to minimize the error that can occur during model training due to pathological stains. The normalized dataset was fed into the ResNet-34 for the classification of normal and invasive breast cancer images. ResNet-34 gave 94% accuracy, 93% F Score, 95% of model Recall, and 91% precision.

• 한국한의학연구원논문집
• /
• 제13권2호통권20호
• /
• pp.47-52
• /
• 2007

In Oriental medicine, the status of tongue is the important indicator to diagnose one's health, because it represents physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive, therefore, tongue diagnosis is one of the most widely used in Oriental medicine. But tongue diagnosis is affected by examination circumstances a lot. It depends on a light source, degrees of an angle, doctor's condition and so on. So it is not easy to make an objective and standardized tongue diagnosis. As part of way to solve this problem, in this study, we tried to design a discriminant function for white and yellow coating with multi-dimensional color vectors. There were 62 subjects involved in this study, among them 48 subjects diagnosed as white-coated tongue and 14 subjects diagnosed as yellow-coated tongue by oriental doctors. And their tongue images were acquired by a well-made Digital Tongue Diagnosis System. From those acquired tongue images, each coating section were extracted by oriental doctors, and then mean values of multi -dimensional color vectors in each coating section were calculated. By statistical analysis, two significant vectors, R in RGB space and H in HSV space, were found that they were able to describe the difference between white coating section and yellow coating section very well. Using these two values, we designed the discriminant function for coating classification and examined how good it works. As a result, the overall accuracy of coating classification was 98.4%. We can expect that the discriminant function for other coatings can be obtained in a similar way. Furthermore, if an automated segmentation algorithm of tongue coating is combined with these discriminant functions, an automated tongue coating diagnosis can be accomplished.

• 한국멀티미디어학회논문지
• /
• 제20권2호
• /
• pp.134-143
• /
• 2017

Machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines. Generally, it is very difficult to diagnose a machine fault by conventional methods based on mathematical models because of the complexity of the real world systems and the obvious existence of nonlinear factors. This study develops an automatic machine fault diagnosis system that uses pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The sounds emitted by the operating machine, a drill in this case, are obtained and analyzed for the different operating conditions. The specific machine conditions considered in this research are the undamaged drill and the defected drill with wear. Principal component analysis is first used to reduce the dimensionality of the original sound data. The first principal components are then used as the inputs of a neural network based classifier to separate normal and defected drill sound data. The results show that the proposed PCA-ANN method can be used for the sounds based automated diagnosis system.

• 인터넷정보학회논문지
• /
• 제11권3호
• /
• pp.65-74
• /
• 2010

유비쿼터스 헬스케어에서 지능형 의사결정지원 및 빠른 진단결과를 제공하기 위한 자동진단은 일반적으로 에이전트 시스템에 의해 수행된다. 본 연구에서는 이동에이전트기술을 사용하여 저 부하 노드에 효율적으로 프로세스를 이주시켜 부하를 분산시키도록 유비쿼터스 헬스케어시스템을 설계하였다. 또한 실시간 자동진단시스템을 지원하는 이동에이전트 중심의 유비쿼터스 헬스케어 기술을 위한 프레임워크를 제시하며, 효율적인 자원활용을 고려하여, 노드들 내에 있는 프로세스의 부하분산을 위한 균형화된 클러스터링을 제안한다. 제안한 알고리즘은 시스템의 부하분산이 최소화될 때까지 과부하된 노드를 선택하여 프로세스를 가까운 노드에 이주시킨다. 제안한 균형화 클러스터링은, 가까운 노드에 이주시킴으로써 메시지오버헤드를 감안할 때, 효율적으로 프로세스를 모든 노드에 분산시킨다.

• 한국항공운항학회지
• /
• 제16권2호
• /
• pp.1-11
• /
• 2008

Increasing demand for improved reliability and survivability of mission-critical systems is driving the development of health monitoring and Automated Contingency Management (ACM) systems. An ACM system is expected to adapt autonomously to fault conditions with the goal of still achieving mission objectives by allowing some degradation in system performance within permissible limits. ACM performance depends on supporting technologies like sensors and anomaly detection, diagnostic/prognostic and reasoning algorithms. This paper presents the development of a generic prototype test bench software framework for developing and validating ACM systems for advanced propulsion systems called the Propulsion ACM (PACM) Test Bench. The architecture has been implemented for a Monopropellant Propulsion System (MPS) to demonstrate the validity of the approach. A Simulink model of the MPS has been developed along with a fault injection module. It has been shown that the ACM system is capable of mitigating the failures by searching for an optimal strategy. Furthermore, the concepts of Validation and Verification (V&V) of such systems are introduced with relevant examples.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1995년도 추계학술대회
• /
• pp.201-204
• /
• 1995

In this study, we proposed an algorithm for P-wave detection. It is essential to decide the existence of P-wave and to extract some parameter about P-wave in automated ECG interpreter. Especially this paper describes the detection and estimation of three case, artrial flutter, coupled and non-coupled, which are very crucial things in ECG diagnosis. The performance of algorithm is showed by applying it to CSE(Common Standards for Quantative Electrocardiography) database.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1997년도 추계학술대회
• /
• pp.579-582
• /
• 1997

The two dimnesional echocardiography is widely used to evaluate regional wall motion abnormaility, because of its abilities to depict left ventricluar wall motion. A new method, color kinesis is a technology or echocardiographic assessment of left ventricular wall motion. In this paper, we proposed a algorithm or color kinesis which is based on acoustic quantification and automatically detects endocardial motion during systole on a frame-by-frame basis. The echocardiograms were obtained in the short-axis views in normal subjects. Automated edge detection and endocardial contour tracing algorithm was applied to each frames, quantitative analysis based on segmentation was performed, and pre-defined color overlays superimposed on the gray scale images. Segmental analysis of color kinesis provided automated, quantitative diagnosis of regional wall motion abnormality.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1996년도 추계학술대회
• /
• pp.286-288
• /
• 1996

To make correct prognoses in the area of orthodontics, dentists use cephalometric analysis methods. Currently, most of them involve two main steps: initial diagnosis and treatment establishment. Currently, dentists work manually on X-ray film to measure the cephalogmetric parameters. The work is tedious and time-consuming, and sometimes produces incorrect results. We developed an automated cephalometric analysis system, in which dentists can easily locate reference points needed for the analysis and get the results almost at the same time.

• 한국정밀공학회지
• /
• 제14권1호
• /
• pp.108-118
• /
• 1997

The heterarchical structure provides a more attractive solution to the conventional hierarchical structure as the density and level of distrubution of computing resources in manufacturing system expands. Tracing the evolution of control structures for automated manufacturing systems, this paper discusses the design principles for heterarchical system to reduce complexity, increase extendability, flexible configurability and suggests a good example of real-time adaptation using the concept of intelligent agent of manufac- turing entities and fault diagmosis system.

• Tuberculosis and Respiratory Diseases
• /
• 제44권5호
• /
• pp.1011-1018
• /
• 1997

연구배경 : 이 연구의 목적은 자동생검장치를 이용한 경피적 폐생검의 유용성과 안전성에 대하여 알아보기 위함이다. 방 법 : 저자들은 폐종괴를 가진 114명의 환자를 대상으로 18-gauge 자동생검장치(ASAP 18, Microvasive)를 사용하여 경피적 폐생검올 시행하였다. 이중 16명에서는 1회의 반복생검을 하여 총 130예의 폐생검의 이루어졌다. 130예중 83예는 숙련된 방사건과의사에 의하여 나머지 47예는 비교적 덜 숙련된 여러명의 방사선과의사들에 의하여 생검이 시행되었다. 모든 생검은 투시유도하에 시술되었다. 결 과 : 130예중 128예(98%)에서 2mm 이상의 충분한 검체를 얻을 수 있었다. 전체 114 명중 97명(85%)에서 조직학적 진단을 내릴 수 있었으며, 이중 악성질환을 가진 89명중 78명(88%)과 양성질환을 가진 21명 중 19명(90%)에서 특이적 진단을 얻을 수 있었다. 조직학적 진단이 가능하였던 폐암에서는 전례(74/74)에서 소세포암과 비소세포암의 구분이 가능하였다. 진단에 필요한 조직을 얻는데 숙련자와 비숙련자간의 유의한 차이는 없었다. 총 130예중 생검후 13예(10%)에서 기흉이 발생하였으나 이중 2예(2%)에서만 삽관술을 필요로 하였고, 7예(5%)에서 경미한 객혈이 발생하였으나 치료를 요한 경우는 1예도 없었다. 결 론 : 자동생검장치를 이용한 경피적 폐생검은 악성과 양성 폐질환의 특이적 진단을 내리는데 유용한 검사이며 합병증의 발생 빈도도 낮은 안전한 시술이다.