BACKGROUND: We have described an objective and reproducible classification method for grading malignancy in the Feulgen stained bladder carcinoma. To create an optimized classifier for malignancy grading of histological bladder carcinoma cell images, it is necessary to extract the features that accurately describle the order/disorder of the nuclear variation and to evaluate the significance of the features. Above all, features selection considered about the correlation of features is very important, because the performance of the classification method depends on the selected features. METHODS: First, we acquired 40 representative histological bladder carcinoma cell images from each of four groups (Grade 1, Grade 2A, Grade 2B, Grade 3) and extracted morphology features, texture features and the texture features of wavelet transformed images. Second, we evaluated the significance of the extracted features using variance analysis. Third, we created classifiers for each selected feature and its combination set using discriminant analysis. Finally, we compared and analyzed the correct classification rate of each classifer. RESULTS: The optimized classifier was created from the combination of morphology features, texture features and the texture features of wavelet transformed images. CONCLUSIONS: We found that the correlation of features is more important than one feature's great significance in grading the malignancy of bladder carcinoma, and we have confirmed that the correct classification rate is determined by feature extractin, feature evaluation and feature selection.
Classification ; Multivariate Analysis ; Urinary Bladder Neoplasms ; Urinary Bladder* ; Wavelet Analysis

OBJECTIVE: We have developed breast tumor image retrieval system using content-based retrieval method. It compares the breast tumor image with Fibrocystic Change images, Ductal Carcinoma in Situ images and Invasive Ductal Carcinoma images and find most similar one. Since the final diagnosis for breast tumor image is done only by pathologist manually, this system can provide the objectivity and the reproducibility for determining and diagnosing the breast tumor. METHODS: The breast tumor image features used in the content-based image retrieval are color feature, texture feature and texture features of wavelet transformed images. And the system can be accessed through the internet. We used Windows 2003 as an operating system, Internet Information Server 6.0 as Web a server and ms-sql server 2000 as a database server. Also we use ActiveX Data Object to connect database easily. RESULT: We evaluated the recall and precision performance of the system according to the combinations of feature types and usage of partial or whole image. Results showed that the use of multiple features and whole image gave consistently higher rates compared to the use of single feature and partial image. CONCLUSION: This retrieval system can help pathologist determine the type of breast tumor more efficiently. Also it is working based on the internet, we can use it for researching and teaching in pathology later.
Breast Neoplasms* ; Breast* ; Carcinoma, Ductal ; Carcinoma, Intraductal, Noninfiltrating ; Diagnosis ; Internet* ; Pathology ; Wavelet Analysis

Telepathology systems will be common systems in hospitals. The two systems were designed and implemented in web environments for test. One was implemented with the Common Object Request Broker Architecture (CORBA) technique. The other system was implemented in the form of ActiveX. The histopathological materials were stained by Hematoxylin and Eosin. By the Donpisha CCD camera attached to an Olympus BX-51 optical microscope 180 color images come to be acquired. For evaluation of the systems, transmission times and telediagnosis concordance rates were measured. Image processing ability was tested using two telepathology systems. For the local area test, system I using CORBA had measured image transmission times of 0.1 s, 0.2 s, and 0.4 s at the file sizes of 100 K byte, 900 K byte and 3.6 M byte respectively. Transmission times for system II using Component Object Model (COM) were slightly slower, ranging from 0.02 s to 0.05 s. In the long distance area test, system II transmission times were 0.5 s, 0.8 s, and 2.0 s. The overall concordance rate of telediagnosis for the 180 images was 78.3%. In this study, we compared our systems about image transmission, and processing for the further development of system configurations.
Eosine Yellowish-(YS) ; Hematoxylin ; Internet* ; Telepathology*

OBJECTIVES: A new software (Cardiac SPECT Analyzer: CSA) was developed for quantification of volumes and ejection fraction on gated myocardial SPECT. Volumes and ejection fraction by CSA were validated by comparing with those quantified by Quantitative Gated SPECT (QGS) software. MATERIALS AND METHODS: Gated myocardial SPECT was performed in 40 patients with ejection fraction from 15% to 85%. In 26 patients, gated myocardial SPECT was acquired again with the patients in situ. A cylinder model was used to eliminate noise semi-automatically and profile data was extracted using Gaussian fitting after smoothing. The boundary points of endo- and epicardium were found using an iterative learning algorithm. Enddiastolic (EDV) and endsystolic volumes (ESV) and ejection fraction (EF) were calculated. These values were compared with those calculated by QGS and the same gated SPECT data was repeatedly quantified by CSA and variation of the values on sequential measurements of the same patients on the repeated acquisition. RESULTS: From the 40 patient data, EF, EDV and ESV by CSA were correlated with those by QGS with the correlation coefficients of 0.97, 0.92, 0.96. Two standard deviation (SD) of EF on Bland Altman plot was 10.1%. Repeated measurements of EF, EDV, and ESV by CSA were correlated with each other with the coefficients of 0.96, 0.99, and 0.99 for EF, EDV and ESV respectively. On repeated acquisition, reproducibility was also excellent with correlation coefficients of 0.89, 0.97, 0.98, and coefficient of variation of 8.2%, 5.4mL, 8.5mL and 2SD of 10.6%, 21.2mL, and 16.4mL on Bland Altman plot for EF, EDV and ESV. CONCLUSION: We developed the software of CSA for quantification of volumes and ejection fraction on gated myocardial SPECT. Volumes and ejection fraction quantified using this software was found valid for its correctness and precision.
Humans ; Learning ; Noise ; Pericardium ; Tomography, Emission-Computed, Single-Photon*

The diagnosis of atrial septal defect by transthoracic echocardiography remains difficult in a small subset of patients because of either suboptimal acoustic windows or unusual anatomy, for example, fenestrated defects. wer report the case of a 52-year-old woman with a fenestratdd atrial septal aneurysm that was incompletely visualized by transthoracic echocardiography. Subsequent transesophageal echocardiography demonstrated atrial septal defect and two fenestrations within the atrial septal aneurysm with left-to-right shunting. All echocardiographic findings were confirmed at surgery. This case demonstrates the addinional diagnostic accuracy of transesophageal echocardiography for detecting disease of the atrial septum.
Acoustics ; Aneurysm* ; Atrial Septum ; Diagnosis ; Echocardiography ; Echocardiography, Transesophageal ; Female ; Heart Septal Defects, Atrial* ; Humans ; Middle Aged

Objectives: A primary brain tumor starts to grow from brain cells, and it occurs as a result of errors in the DNA of normal cells. Therefore, this study was carried out to analyze the two-dimensional (2D) texture, morphology, and statistical features of brain tumors and to perform a classification using artificial intelligence (AI) techniques. Methods: AI techniques can help radiologists to diagnose primary brain tumors without using any invasive measurement techniques. In this paper, we focused on deep learning (DL) and machine learning (ML) techniques for texture, morphological, and statistical feature classification of three tumor types (namely, glioma, meningioma, and pituitary). T1-weighted magnetic resonance imaging (MRI) 2D scans were used for analysis and classification (multiclass and binary). A total of 102 features were calculated for each tumor, and the 20 most significant features were selected using the three-step feature selection method, which included removing duplicate features, Pearson correlations, and recursive feature elimination. Results: From the predicted results of multiclass and binary classification, a long short-term memory binary classification (glioma vs. meningioma) showed the best performance, with an average accuracy, recall, precision, F1-score, and kappa coefficient of 97.7%, 97.2%, 97.5%, 97.0%, and 94.7%, respectively. Conclusions The early diagnosis of primary brain tumors is very important because it can be the key to effective treatment. Therefore, this research presents a method for early diagnoses by effectively classifying three types of primary brain tumors.

PURPOSE: Optical molecular luminescence imaging is widely used for detection and imaging of bio-photons emitted by luminescent luciferase activation. The measured photons in this method provide the degree of molecular alteration or cell numbers with the advantage of high signal-to-noise ratio. To extract useful information from the measured results, the analysis based on a proper quantification method is necessary. In this research, we propose a quantification method presenting linear response of measured light signal to measurement time. MATERIALS AND METHODS: We detected the luminescence signal by using lab-made optical imaging equipment of animal light imaging system (ALIS) and different two kinds of light sources. One is three bacterial light-emitting sources containing different number of bacteria. The other is three different non-bacterial light sources emitting very weak light. By using the concept of the candela and the flux, we could derive simplified linear quantification formula. After experimentally measuring light intensity, the data was processed with the proposed quantification function. RESULTS: We could obtain linear response of photon counts to measurement time by applying the pre-determined quantification function. The ratio of the re-calculated photon counts and measurement time present a constant value although different light source was applied. CONCLUSION: The quantification function for linear response could be applicable to the standard quantification process. The proposed method could be used for the exact quantitative analysis in various light imaging equipments with presenting linear response behavior of constant light emitting sources to measurement time.
Animals ; Bacteria ; Cell Count ; Enzyme Multiplied Immunoassay Technique ; Imidazoles ; Light ; Luciferases ; Luminescence ; Nitro Compounds ; Optical Imaging ; Photons ; Signal-To-Noise Ratio

BACKGROUND: To characterize the clinical features and determine the prognostic factors of severe community-acquired pneumonia. This study is the first of its kind in Korea. METHODS: Recruited were 40 patients diagnosed as severe community-acquired pneumonia in Hallym University Hospital from January 1, 1989 through July 31, 1996. Patients were analysed retrospectively for age, sex, underlying disease, respiration rate, hypoxemia, requirement of mechanical ventilation, involvement on chest radiograph, shock, and the serum concentration of BUN and albumin. All parameters were compared between survived and dead group. RESULTS: Male to female ratio was 2.07 : 1. The mean age was 63.1+/-l7.5years(range 25-90years) with 65% of patients aged equal to or more than 60. The major underlying diseases were old pulmonary tuberculosis(12.5%), chronic obstructive pulmonary disease(7.5%), bronchial asthma(5%), bronchiectasis(2.5%), and diabetes mellitus(22.5%). Microbiologic diagnosis was made in 26 out of 40 patients(65%). The most common causative organism was S. Pneumoniae(17.5%, 7/40) followed by S. aureus(15.0%, 6/40), K. Pncumoniac(12.5%, 5/40), M. tubercut osis(7.5%, 3/40), H. influenzae(2.5%, 1/40), coagulase negative staphylococcus(2.5%, 1/40), P aeruginosa(2.5%, 1/40), E. cloaceae(2.5%, 1/40), and E. coli(2.5%, 1/40). M. Pneumoniae was detected in no patient. The most frequent drugs administered in single or combination therapy were aminoglycosides(75%, 30/40), second- and third-generation cephalosporin(40%, 16/40 and 27.5%, 11/40), macro]ides(27.5%, 11/40), and amoxicillin/clavulanic acid(22.5%, 9/40). Of the 40 patients, 14 died of severe community-acquired pneumonia(37.S%). Among them, seven patients (50%) expired within 72h of hospital arrival. According to multivariate analysis, mortality was significantly associated with requirement of mechanical ventilation, bilateral pulmonary involvement, and serum albumin < or = 3.0g/dl. CONCLUSION: An understanding of the clinical charateristics and prognostic factors in severe community-acquired pneumonia identified in this study will optimize therapeutic approach in this disease and help decreasing its notorious mortality rate.
Anoxia ; Coagulase ; Diagnosis ; Female ; Humans ; Korea ; Male ; Mortality ; Multivariate Analysis ; Pneumonia* ; Prognosis ; Radiography, Thoracic ; Respiration, Artificial ; Respiratory Rate ; Retrospective Studies ; Serum Albumin ; Shock

No abstract available.

PURPOSE: Regional contractility can be calculated using the regional volume change of left ventricle measured by gated myocardial SPECT image and curve of central artery pressure obtained from radial artery pressure data. In this study, a program to obtain the regional contractility was developed, and reproducibility of regional contractility measurement was assessed. MATERIALS AND METHODS: Seven patients (male: female=5: 2, 58+/-11.9 years) with coronary artery diseases underwent gated Tc-99m MIBI myocardial SPECT twice without delay between two scans. Regional volume change of left ventricle was estimated using CSA (Cardiac SPECT Analyzer) software developed in this study. Regional contractility was iteratively estimated from the time-elastance curve obtained using the time-pressure curve and regional time-volume curve. Reproducibility of regional contractility measurement assessed by comparing the contractility values measured twice from the same SPECT data and by comparing those measured from the pair of SPECT data obtained from a same patient. RESULTS: Measured regional contractility was 3.36 +/- 3.38 mmHg/mL using 15-segment model, 3.16 +/- 2.25 mmHg/mL using 7-segment model, and 3.11 +/- 2.57 mmHg/mL using 5-segment model. The harmonic average of regional contractility value was almost identical to the global contractility. Correlation coefficient of regional contractility values measured twice from the same data was greater than 0.97 for all models, and two standard deviations of contractility difference on Bland Altman plot were 1.5%, 1.0%, and 0.9% for 15-, 7-, and 5-segment models, respectively. Correlation coefficient of regional contractility values measured from the pair of SPECT data obtained from a same patient was greater than 0.95 for all models, and two standard deviations on Bland Altman plot were 2.2%, 1.0%, and 1.2%. CONCLUSION: Regional contractility of left ventricle measured using developed software in this study was reproducible. Regional contractility of left ventricle will be a new useful index for myocardial function after analysis of the clinical data.
Arteries ; Coronary Artery Disease ; Heart Ventricles* ; Humans ; Radial Artery ; Tomography, Emission-Computed, Single-Photon*