Automated diagnosis of human intestinal parasites using optical microscopy images

Intestinal parasitosis constitutes a serious health problem in most tropical countries. The diagnosis of enteroparasites in laboratory routine relies on the examination of stool samples using optical microscopy and the error rates usually range from moderate to high. Approaches based on automatic image analysis have been proposed, but the methods are usually specific for some species, some of them are computationally expensive, and image acquisition and focus are manual. We present a solution to automate the diagnosis of the 15 most common species of enteroparasites in Brazil, using a sensitive parasitological technique, a motorized microscope with digital camera for automatic image acquisition and focus, and fast image analysis methods. The results indicate that our solution is effective and suitable for laboratory routine, in which the exam must be concluded in a few minutes. © 2013 IEEE.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

Control point strategy and its automated diagnosis,

Thesis (M.S.)--University of Illinois at Urbana-Champaign.

Computational methods for the detection of facial palsy

We are developing a telemedicine application which offers automated diagnosis of facial (Bell's) palsy through a Web service. We used a test data set of 43 images of facial palsy patients and 44 normal people to develop the automatic recognition algorithm. Three different image pre-processing methods were used. Machine learning techniques (support vector machine, SVM) were used to examine the difference between the two halves of the face. If there was a sufficient difference, then the SVM recognized facial palsy. Otherwise, if the halves were roughly symmetrical, the SVM classified the image as normal. It was found that the facial palsy images had a greater Hamming Distance than the normal images, indicating greater asymmetry. The median distance in the normal group was 331 (interquartile range 277-435) and the median distance in the facial palsy group was 509 (interquartile range 334-703). This difference was significant (P

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

A new, automated, four-colour interphase FISH approach for the simultaneous detection of specific aneuploidies of diagnosis and prognosis significance in high hyperdiploid ALL

In hyperdiploid acute lymphoblastic leukaemia (ALL), the simultaneous occurrence of specific aneuploidies confers a more favourable outcome than hyperdiploidy alone. Interphase (I) FISH complements conventional cytogenetics (CC) through its sensitivity and ability to detect chromosome aberrations in non-dividing cells. To overcome the limits of manual I-FISH, we developed an automated four-colour I-FISH approach and assessed its ability to detect concurrent aneuploidies in ALL. I-FISH was performed using centromeric probes for chromosomes 4, 6, 10 and 17. Parameters established for automatic nucleus selection and signal detection were evaluated (3 controls). Cut-off values were determined (10 controls, 1000 nuclei/case). Combinations of aneuploidies were considered relevant when each aneuploidy was individually significant. Results obtained in 10 ALL patients (1500 nuclei/patient) were compared with those by CC. Various combinations of aneuploidies were identified. All clones detected by CC were observed by I-FISH. I-FISH revealed numerous additional abnormal clones, ranging between 0.1 % and 31.6%, based on the large number of nuclei evaluated. Four-colour automated I-FISH permits the identification of concurrent aneuploidies of prognostic significance in hyperdiploid ALL. Large numbers of cells can be analysed rapidly by this method. Owing to its high sensitivity, the method provides a powerful tool for the detection of small abnormal clones at diagnosis and during follow up. Compared to CC, it generates a more detailed cytogenetic picture, the biological and clinical significance of which merits further evaluation. Once optimised for a given set of probes, the system can be easily adapted for other probe combinations.

Introduction of an automated system for the diagnosis and quantification of hepatitis B and hepatitis C viruses.

Hepatitis B virus (HBV) and Hepatitis C virus (HCV) infections pose major public health problems because of their prevalence worldwide. Consequently, screening for these infections is an important part of routine laboratory activity. Serological and molecular markers are key elements in diagnosis, prognosis and treatment monitoring for HBV and HCV infections. Today, automated chemiluminescence immunoassay (CLIA) analyzers are widely used for virological diagnosis, particularly in high-volume clinical laboratories. Molecular biology techniques are routinely used to detect and quantify viral genomes as well as to analyze their sequence; in order to determine their genotype and detect resistance to antiviral drugs. Real-time PCR, which provides high sensitivity and a broad dynamic range, has gradually replaced other signal and target amplification technologies for the quantification and detection of nucleic acid. The next-generation DNA sequencing techniques are still restricted to research laboratories.The serological and molecular marker methods available for HBV and HCV are discussed in this article, along with their utility and limitations for use in Chronic Hepatitis B (CHB) diagnosis and monitoring.

Effect of Disease Severity on the Performance of Cirrus Spectral-Domain OCT for Glaucoma Diagnosis

PURPOSE. To evaluate the effect of disease severity on the diagnostic accuracy of the Cirrus Optical Coherence Tomograph (Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, CA) for glaucoma detection. METHODS. One hundred thirty-five glaucomatous eyes of 99 patients and 79 normal eyes of 47 control subjects were recruited from the longitudinal Diagnostic Innovations in Glaucoma Study (DIGS). The severity of the disease was graded based on the visual field index (VFI) from standard automated perimetry. Imaging of the retinal nerve fiber layer (RNFL) was obtained using the optic disc cube protocol available on the Cirrus HD-OCT. Pooled receiver operating characteristic (ROC) curves were initially obtained for each parameter of the Cirrus HD-OCT. The effect of disease severity on diagnostic performance was evaluated by fitting an ROC regression model, with VFI used as a covariate, and calculating the area under the ROC curve (AUCs) for different levels of disease severity. RESULTS. The largest pooled AUCs were for average thickness (0.892), inferior quadrant thickness (0.881), and superior quadrant thickness (0.874). Disease severity had a significant influence on the detection of glaucoma. For the average RNFL thickness parameter, AUCs were 0.962, 0.932, 0.886, and 0.822 for VFIs of 70%, 80%, 90%, and 100%, respectively. CONCLUSIONS. Disease severity had a significant effect on the diagnostic performance of the Cirrus HD-OCT and thus should be considered when interpreting results from this device and when considering the potential applications of this instrument for diagnosing glaucoma in the various clinical settings. (Invest Ophthalmol Vis Sci. 2010;51:4104-4109) DOI:10.1167/iovs.094716

Automated regional myocardial displacement for facilitating the interpretation of dobutamine echocardiography

Quantification of stress echocardiography may overcome the training requirements and subjective nature of visual wall motion score (WMS) assessment, but quantitative approaches may be difficult to apply and require significant time for image processing. The integral of long-axis myocardial velocity is displacement, which may be represented as a color map over the left ventricular myocardium. This study was designed to explore the feasibility and accuracy of measuring long-axis myocardial displacement, derived from tissue Doppler, for the detection of coronary artery disease (CAD) during dobutamine stress echocardiography (DBE). One hundred thirty patients underwent standard DBE, including 30 patients at low risk of CAD, 30 patients with normal coronary angiography (both groups studied to define normal ranges of displacement), and 70 patients who underwent coronary angiography in whom the accuracy of normal ranges was tested. Regional myocardial displacement was obtained by analysis of color tissue Doppler apical images acquired at peak stress. Displacement was compared with WMS, and with the presence of CAD by angiography. The analysis time was 3.2 +/- 1.5 minutes per patient. Segmental displacement was correlated with wall motion (normal 7.4 +/- 3.2 mm, ischemia 5.8 +/- 4.2 mm, viability 4.6 +/- 3.0 mm, scar 4.5 +/- 3.5 mm, p <0.001). Reversal of normal base-apex displacement was an insensitive (19%) but specific (90%) marker of CAD. The sum of displacements within each vascular territory had a sensitivity and specificity of 89% and 79%, respectively, for prediction of significant CAD, compared with 86% and 78%, respectively, for WMS (p = NS). The displacements in the basal segments had a sensitivity and specificity of 83% and 78%, respectively (p = NS). Regional myocardial displacement during DBE is feasible and offers a fast and accurate method for the diagnosis of CAD. (C),2002 by Excerpta Medica, Inc.

Comparison between the HemoCue® and an automated counter for measuring hemoglobin

To determine the precision and agreement of the hemoglobin (Hb) measurements in capillary and venous blood samples by the HemoCue® and an automated counter. Hb was determined by both equipaments in blood samples of 29 pregnant women. The HemoCue® showed low repeatability of Hb measurements in duplicate in capillary (CR=0.53 g/dL, CV=13.6%) and venous blood (CR=0.53 g/dL, CV=13.6%). Hb measurements in capillary blood were higher than those in venous blood (12.4 and 11.7 g/dL, respectively; p<0.05). There was high agreement between Hb in capillary blood by the HemoCue® and in venous blood by the counter (r icc=0.86; p<0.01), and also between the diagnosis of anemia by both equipments (k=0.81; p<0.01). The HemoCue® seems to be more appropriate for capillary blood and require training of the measurers.

Laboratory detection of respiratory viruses by automated techniques.

Advances in clinical virology for detecting respiratory viruses have been focused on nucleic acids amplification techniques, which have converted in the reference method for the diagnosis of acute respiratory infections of viral aetiology. Improvements of current commercial molecular assays to reduce hands-on-time rely on two strategies, a stepwise automation (semi-automation) and the complete automation of the whole procedure. Contributions to the former strategy have been the use of automated nucleic acids extractors, multiplex PCR, real-time PCR and/or DNA arrays for detection of amplicons. Commercial fully-automated molecular systems are now available for the detection of respiratory viruses. Some of them could convert in point-of-care methods substituting antigen tests for detection of respiratory syncytial virus and influenza A and B viruses. This article describes laboratory methods for detection of respiratory viruses. A cost-effective and rational diagnostic algorithm is proposed, considering technical aspects of the available assays, infrastructure possibilities of each laboratory and clinic-epidemiologic factors of the infection.

Evaluation of three automated systems for susceptibility testing of enterobacteria containing qnrB, qnrS, and/or aac(6')-Ib-cr.

The accuracy of the MicroScan WalkAway, BD Phoenix, and Vitek-2 systems for susceptibility testing of quinolones and aminoglycosides against 68 enterobacteria containing qnrB, qnrS, and/or aac(6 ')-Ib-cr was evaluated using reference microdilution. Overall, one very major error (0.09%), 6 major errors (0.52%), and 45 minor errors (3.89%) were noted.

Automated four-color interphase fluorescence in situ hybridization approach for the simultaneous detection of specific aneuploidies of diagnostic and prognostic significance in high hyperdiploid acute lymphoblastic leukemia.

In high hyperdiploid acute lymphoblastic leukemia (ALL), the concurrence of specific trisomies confers a more favorable outcome than hyperdiploidy alone. Interphase fluorescence in situ hybridization (FISH) complements conventional cytogenetics (CC) through its sensitivity and ability to detect chromosome aberrations in nondividing cells. To overcome the limits of manual I-FISH, we developed an automated four-color I-FISH approach and assessed its ability to detect concurrent aneuploidies in ALL. I-FISH was performed using centromeric probes for chromosomes 4, 6, 10, and 17. Parameters established for nucleus selection and signal detection were evaluated. Cutoff values were determined. Combinations of aneuploidies were considered relevant when each aneuploidy was individually significant. Results obtained in 10 patient samples were compared with those obtained with CC. Various combinations of aneuploidies were identified. All clones detected by CC were observed also by I-FISH, and I-FISH revealed numerous additional abnormal clones in all patients, ranging from < or =1% to 31.6% of cells analyzed. We conclude that four-color automated I-FISH permits the identification of concurrent aneuploidies of potential prognostic significance. Large numbers of cells can be analyzed rapidly. The large number of nuclei scored revealed a high level of chromosome variability both at diagnosis and relapse, the prognostic significance of which is of considerable clinical interest and merits further evaluation.

Infornut® Process; improves accessibility to diagnosis and nutritional support for the malnourished hospitalized patient; impact on management indicators; two-year assessment.

Introduction: The high prevalence of disease-related hospital malnutrition justifies the need for screening tools and early detection in patients at risk for malnutrition, followed by an assessment targeted towards diagnosis and treatment. At the same time there is clear undercoding of malnutrition diagnoses and the procedures to correct it Objectives: To describe the INFORNUT program/ process and its development as an information system. To quantify performance in its different phases. To cite other tools used as a coding source. To calculate the coding rates for malnutrition diagnoses and related procedures. To show the relationship to Mean Stay, Mortality Rate and Urgent Readmission; as well as to quantify its impact on the hospital Complexity Index and its effect on the justification of Hospitalization Costs. Material and methods: The INFORNUT® process is based on an automated screening program of systematic detection and early identification of malnourished patients on hospital admission, as well as their assessment, diagnoses, documentation and reporting. Of total readmissions with stays longer than three days incurred in 2008 and 2010, we recorded patients who underwent analytical screening with an alert for a medium or high risk of malnutrition, as well as the subgroup of patients in whom we were able to administer the complete INFORNUT® process, generating a report for each.

A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis.

Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG.