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Biomedical subjects

D Cavouras

Publications and source records attributed to D Cavouras.

At least 19 recordsLinked to original sources
PubMed2006

A hybrid multi-scale model for thyroid nodule boundary detection on ultrasound images.

A hybrid model for thyroid nodule boundary detection on ultrasound images is introduced. The segmentation model combines the advantages of the "á trous" wavelet transform to detect sharp gray-level variations and the efficiency of the Hough transform to discriminate the region of interest within an environment with excessive structural noise. The proposed method comprise three major steps: a wavelet edge detection procedure for speckle reduction and edge map estimation, based on local maxima representation. Subsequently, a multiscale structure model is utilised in order to acquire a contour representation by means of local maxima chaining with similar attributes to form significant structures. Finally, the Hough transform is employed with 'a priori' knowledge related to the nodule's shape in order to distinguish the nodule's contour from adjacent structures. The comparative study between our automatic method and manual delineations demonstrated that the boundaries extracted by the hybrid model are closely correlated with that of the physicians. The proposed hybrid method can be of value to thyroid nodules' shape-based classification and as an educational tool for inexperienced radiologists.

Algorithms↗
PubMed2006

Osteoarthritis severity of the hip by computer-aided grading of radiographic images.

A computer-aided classification system was developed for the assessment of the severity of hip osteoarthritis (OA). Sixty-four radiographic images of normal and osteoarthritic hips were digitized and enhanced. Employing the Kellgren and Lawrence scale, the hips were grouped by three experienced orthopaedists into three OA-severity categories: Normal, Mild/Moderate and Severe. Utilizing custom-developed software, 64 ROIs corresponding to the radiographic Hip Joint Spaces were manually segmented and novel textural features were generated. These features were used in the design of a two-level classification scheme for characterizing hips as normal or osteoarthritic (1st level) and as of Mild/Moderate or Severe OA (2nd level). At each classification level, an ensemble of three classifiers was implemented. The proposed classification scheme discriminated correctly all normal hips from osteoarthritic hips (100% accuracy), while the discrimination accuracy between Mild/Moderate and Severe osteoarthritic hips was 95.7%. The proposed system could be used as a diagnosis decision-supporting tool.

Aged↗
PubMed2006

Assessing hip osteoarthritis severity utilizing a probabilistic neural network based classification scheme.

A computer-based classification system is proposed for the characterization of hips from pelvic radiographs as normal or osteoarthritic and for the discrimination among various grades of osteoarthritis (OA) severity. Pelvic radiographs of 18 patients with verified unilateral hip OA were evaluated by three experienced physicians, who assessed OA severity employing the Kellgren and Lawrence scale as: normal, mild/moderate and severe. Five run-length, 75 Laws' and 5 novel textural features were extracted from the digitized radiographic images of each patient's osteoarthritic and contralateral normal hip joint spaces (HJSs). Each one of the three sets of textural features (run-lengths, Laws' and novel features) was separately utilized for assigning hips into the three OA severity categories, by means of a probabilistic neural network (PNN) classifier based hierarchical tree structure. The highest classification accuracy (100%) for characterizing hips as normal, of mild/moderate or of severe OA was obtained for the novel textural features set. Additionally, the novel textural features were used to design a mathematical regression model for providing a quantitative estimation of OA severity. Measured OA severity values, as expressed by HJS-narrowing, correlated highly (r=0.85, p<0.001) with the predicted values by the mathematical regression model. The proposed system may be valuable in OA-patient management.

Aged↗
PubMed2006

A theoretical model evaluating the angular distribution of luminescence emission in X-ray scintillating screens.

The aim of this study was to examine the angular distribution of the light emitted from radiation-excited scintillators in medical imaging detectors. This distribution diverges from Lambert's cosine law and affects the light emission efficiency of scintillators, hence it also affects the dose burden to the patient. In the present study, the angular distribution was theoretically modeled and was used to fit experimental data on various scintillator materials. Results of calculations revealed that the angular distribution is more directional than that predicted by Lambert's law. Divergence from this law is more pronounced for high values of light attenuation coefficient and thick scintillator layers (screens). This type of divergence reduces light emission efficiency and hence it increases the incident X-ray flux required for a given level of image brightness.

Diagnostic Imaging↗
PubMed2005

An image-analysis system based on support vector machines for automatic grade diagnosis of brain-tumour astrocytomas in clinical routine.

An image-analysis system based on the concept of Support Vector Machines (SVM) was developed to assist in grade diagnosis of brain tumour astrocytomas in clinical routine. One hundred and forty biopsies of astrocytomas were characterized according to the WHO system as grade II, III and IV. Images from biopsies were digitized, and cell nuclei regions were automatically detected by encoding texture variations in a set of wavelet, autocorrelation and parzen estimated descriptors and using an unsupervised SVM clustering methodology. Based on morphological and textural nuclear features, a decision-tree classification scheme distinguished between different grades of tumours employing an SVM classifier. The system was validated for clinical material collected from two different hospitals. On average, the SVM clustering algorithm correctly identified and accurately delineated 95% of all nuclei. Low-grade tumours were distinguished from high-grade tumours with an accuracy of 90.2% and grade III from grade IV with an accuracy of 88.3% The system was tested in a new clinical data set, and the classification rates were 87.5 and 83.8%, respectively. Segmentation and classification results are very encouraging, considering that the method was developed based on every-day clinical standards. The proposed methodology might be used in parallel with conventional grading to support the regular diagnostic procedure and reduce subjectivity in astrocytomas grading.

Astrocytoma↗
PubMed2004

Design and implementation of an SVM-based computer classification system for discriminating depressive patients from healthy controls using the P600 component of ERP signals.

A computer-based classification system has been designed capable of distinguishing patients with depression from normal controls by event-related potential (ERP) signals using the P600 component. Clinical material comprised 25 patients with depression and an equal number of gender and aged-matched healthy controls. All subjects were evaluated by a computerized version of the digit span Wechsler test. EEG activity was recorded and digitized from 15 scalp electrodes (leads). Seventeen features related to the shape of the waveform were generated and were employed in the design of an optimum support vector machine (SVM) classifier at each lead. The outcomes of those SVM classifiers were selected by a majority-vote engine (MVE), which assigned each subject to either the normal or depressive classes. MVE classification accuracy was 94% when using all leads and 92% or 82% when using only the right or left scalp leads, respectively. These findings support the hypothesis that depression is associated with dysfunction of right hemisphere mechanisms mediating the processing of information that assigns a specific response to a specific stimulus, as those mechanisms are reflected by the P600 component of ERPs. Our method may aid the further understanding of the neurophysiology underlying depression, due to its potentiality to integrate theories of depression and psychophysiology.

Case-Control Studies↗
PubMed2004

Development of the cubic least squares mapping linear-kernel support vector machine classifier for improving the characterization of breast lesions on ultrasound.

An efficient classification algorithm is proposed for characterizing breast lesions. The algorithm is based on the cubic least squares mapping and the linear-kernel support vector machine (SVM(LSM)) classifier. Ultrasound images of 154 confirmed lesions (59 benign and 52 malignant solid masses, 7 simple cysts, and 32 complicated cysts) were manually segmented by a physician using a custom developed software. Texture and outline features and the SVM(LSM) algorithm were used to design a hierarchical tree classification system. Classification accuracy was 98.7%, misdiagnosing 1 malignant an 1 benign solid lesions only. This system may be used as a second opinion tool to the radiologists.

Breast Diseases↗
PubMed2003

Support vector machines based analysis of brain SPECT images for determining cerebral abnormalities in asymptomatic diabetic patients.

PURPOSE: An image processing method was developed to investigate whether brain SPECT images of patients with diabetes mellitus type II (DMII) and no brain damage differ from those of normal subjects. MATERIALS AND METHODS: Twenty-five DMII patients and eight healthy volunteers underwent brain 99mTc-Bicisate SPECT examination. A semi-automatic method, allowing for physician's interaction, was developed to delineate specific brain regions (ROIs) on the SPECT images. Twenty-eight features from the grey-level histogram and the spatial-dependence matrix were computed from numerous small image-samples collected from each specific ROI. Classification into 'diabetics' and 'non-diabetics' was performed for each ROI separately. The classical least squares-minimum distance (LSMD) classifier and the recently developed support vector machines (SVM) classifier were used. System performance was evaluated by means of the leave-one-out method; one sample was left out, the classifier was trained by the rest of the samples, and the left-out sample was classified. By repeating for all samples, the classifier's performance could be tested on data not incorporated in its design. RESULTS: Highest classification accuracies (LSMD: 97.8%, SVM: 99.1%) were achieved at the right occipital lobule employing two features, the standard deviation and entropy. For the rest of the ROIs classification accuracies ranged between 84.5 and 98.6%. CONCLUSION: Our findings indicate cerebral blood flow disruption in patients with DMII. The proposed system may assist physicians in evaluating cerebral blood flow in patients with DMII undergoing brain SPECT.

Adult↗
PubMed2002

Integrated model for estimating phosphor signal and noise transfer characteristics on medical images: application to CdPO3Cl:Mn phosphor screens.

An integrated model describing the signal and noise transfer characteristics of the objective image quality and information content in phosphor-produced images is presented. In the context of this model, important imaging parameters, namely optical gain, modulation transfer function, noise transfer function, detective quantum efficiency and information capacity were experimentally evaluated using seven laboratory-prepared CdPO3Cl:Mn test phosphor screens of varying coating thickness. This phosphor has been previously shown to exhibit high spectral compatibility properties with the films and optical sensors used in digital imaging systems. Experiments were performed using 50-120 kVp X-rays produced by a medical X-ray unit. Results showed that, for thick screens, optical gain attained peak values close to 200 optical photons per incident X-ray at 50 kVp. The noise transfer function was higher than the modulation transfer function. For the thin screen of 21 mg cm-2, the modulation transfer function was 0.25 at 100 line pairs mm-1, and the corresponding noise transfer function was 0.4. The detection quantum efficiency peak value was 0.22 at 50 kVp. These values are within acceptable performance limits, and, given the phosphor material's high spectral compatibility and medium temporal response, CdPO3Cl:Mn could be considered for use in X-ray detectors of static radiography imaging.

Humans↗
PubMed2002

Acoustic patterns of infant vocalizations expressing emotions and communicative functions.

The present study aimed at identifying the acoustic pattern of vocalizations, produced by 7- to 11-month-old infants, that were interpreted by their mothers as expressing emotions or communicative functions. Participants were 6 healthy, first-born English infants, 3 boys and 3 girls, and their mothers. The acoustic analysis of the vocalizations was performed using a pattern recognition (PR) software system. A PR system not only calculates signal features, it also automatically detects patterns in the arrangement of such features. The following results were obtained: (a) the PR system distinguished vocalizations interpreted as emotions from vocalizations interpreted as communicative functions with an overall accuracy of 87.34%; (b) the classification accuracy of the PR system for vocalizations that convey emotions was 85.4% and for vocalizations that convey communicative functions was 89.5%; and (c) compared to vocalizations that express emotions, vocalizations that express communicative functions were shorter, displayed lower fundamental frequency values, and had greater overall intensity. These findings suggest that in the second half of the first year, infants possess a vocal repertoire that contributes to regulating cooperative interaction with their mothers, which is considered one of the major prerequisites for language acquisition.

Adult↗
PubMed2002

A computer-based diagnostic and prognostic system for assessing urinary bladder tumour grade and predicting cancer recurrence.

PURPOSE: A computer-based system was designed, incorporating subjective criteria employed by pathologists in their usual microscopic observation of tissue samples and measurements of nuclear characteristics, with the purpose of automatically assessing urinary bladder tumour grade and predicting cancer recurrence. MATERIAL AND METHODS: Ninety-two cases with urine bladder carcinoma were diagnosed and followed-up. Forty-seven patients had cancer recurrence. Each case was represented by eight histological (subjective) features, evaluated by pathologists, and thirty-six automatically extracted nuclear features. Grading and prognosis were performed by neural-network based classifiers employing both histological and nuclear features. RESULTS: Employing a combination of histological and nuclear features, highest classification accuracy was 82%, 80.5%, and 93.1% for tumours of grade I, II and III respectively. The prognostic-system, gave a significant prognostic assessment of 72.8% with a confidence of 74.5% that cancer might recur and of 71.1% that might not, employing two histological features and two textural nuclear features. CONCLUSIONS: The system for grading and predicting tumour recurrence may serve as a second opinion tool and features employed for designing the system may be of value to pathologists using descriptive grading systems.

Decision Support Systems, Clinical↗
PubMed2001

Experimental and theoretical assessment of the performance of Gd2O2S:Tb and La2O2S:Tb phosphors and Gd2O2S:Tb-La2O2S:Tb mixtures for X-ray imaging.

The purpose of this work was to investigate and compare the imaging performance of Gd2O2S:Tb and La2O2S:Tb phosphors as well as of Gd2O2S:Tb and La2O2S:Tb mixtures for use in X-ray imaging detectors (intensifying screens). Phosphors were supplied in powder form and were used to prepare test screens. Three types of screens were prepared: Gd2O2S:Tb; (Gd50La50)O2S:Tb; and La2O2S:Tb. Screens were excited by X-rays with tube voltages from 40 to 120 kV and their efficiency (light intensity or light energy flux over exposure) was measured with a photomultiplier and a dosimeter. The light spectrum was also measured with a monochromator. From these measurements, the number of emitted photons per incident X-ray (NEP) and the zero frequency detective quantum efficiency (DQE(0)) of the screens were determined. Additionally, modulation transfer function (MTF) was measured by the square wave response function (SWRF) method. A theoretical model calculating NEP and DQE was also developed to fit experimental data and predict the performance of Gd2O2S:Tb-La2O2S:Tb mixtures by weight from 10-90% to 90-10%. Gd2O2S:Tb screens exhibited highest NEP, DQE, and MTF at tube voltages higher than 55 kV and lower than 45 kV, whereas La2O2S:Tb screens had better NEP, DQE, and MTF within the 45- to 55-kV range. Maximum NEP values were higher than 700 at 100-120 kV while maximum DQE(0) was 0.314 at 80 kV. Gd2O2S:Tb screens are more efficient for high X-ray tube voltage applications (e.g., abdominal imaging, chest radiography, lumbar spine radiography, CT) and for very low voltage applications (e.g., mammography). La2O2S:Tb screens are useful for medium-range X-ray voltages (e.g., pediatric radiography).

Gadolinium↗
PubMed2001

Role of the activator in the performance of scintillators used in X-ray imaging.

The aim of this study was to investigate how the activator type affects the performance of X-ray scintillators. To this aim the behavior of scintillator materials was modeled under X-ray excitation conditions, similar to those used in imaging techniques. The model describes the light emission efficiency, the spectral compatibility with optical detectors (films, photodiodes, and photocathodes), and the imaging capabilities of a scintillating layer. Using the model equations the role of the activator type in scintillator performance was examined. Activators affect some important properties of materials, like the intrinsic X-ray to light conversion efficiency, the spectrum of the emitted light, and the light attenuation coefficients. The performances of a high-efficiency material (Gd2O2S) combined with either Tb3+ or Eu3+ activators were compared. Results showed that the terbium-activated material exhibited high emission efficiency (number of emitted photons per incident X-ray) and modulation transfer function (spatial resolution and image contrast) while the europium activated material showed slightly better signal-to-noise ratio properties at low spatial frequencies. Both materials were found to exhibit high spectral compatibility with currently used modern optical detectors. In conclusion, the choice of activator may improve spectral compatibility, but care must be taken because it may also alter emission efficiency and image quality.

Europium↗
PubMed2001

A theoretical model for calculation of the detective quantum efficiency in granular scintillators.

A theoretical model has been developed for calculating the detective quantum efficiency (DQE) of scintillators, by taking into account the internal structure of granular scintillators often used in medical imaging detectors. Scintillators were considered to consist of N elementary thin layers containing spherical scintillating grains of equal size. Grains were assumed to be regularly distributed within each thin layer, the thickness of the latter being equal to the grain diameter. Values of the X-ray absorption and X-ray attenuation coefficients, of the intrinsic X-ray to light conversion efficiency and of the optical scattering and absorption coefficients were used as input data to the model. Optical scattering and optical absorption coefficients were determined by fitting the model to experimental luminescence data. The model was employed to calculate the detective quantum efficiency of La2O2S:Tb, Y2O2S:Tb, Y2O2S:Eu, ZnSCdS:Ag, ZnSCdS:Au,Cu scintillators. Results of the calculations were found close to values published in previous studies.

Journal Article↗
PubMed2000

Assessment of the gain transfer function of phosphors for application in medical imaging radiation detectors.

OBJECTIVE: to study various phosphors used in detectors of medical imaging systems by the gain transfer function (GTF), defined in terms of X-ray luminescence efficiency, light spectrum and modulation transfer function. MATERIALS AND METHODS: four phosphor materials, La(2)O(2)S:Tb, Y(2)O(2)S:Tb, Y(2)O(2)S:Eu and Y(2)O(3):Eu were used in the form of fluorescent layers prepared in the laboratory. The GTF was determined at 30 kVp and 80 kVp X-ray tube voltages for various phosphor coating weights. RESULTS: La(2)O(2)S:Tb, which was the highest density and effective atomic number phosphor used, was found to exhibit the best GTF performance at 80 kVp. At 30 kVp, the yttrium based phosphors were found of increased performance. This is mainly due to the proximity of the X-ray energy to the K-absorption edge of yttrium at 17 keV. Europium activated phosphors were found to perform very well when combined with the red sensitive film and the silicon photodiode. CONCLUSION: The GTF may be a useful method for comparing and selecting phosphor materials for use in various medical imaging applications.

Diagnostic Imaging↗
PubMed2000

Assessing the information content of phosphor produced medical images: application to Zn2SiO4:Mn phosphor.

In this study a method to assess the information content of medical images produced by phosphors is described. The optical signal emitted by the phosphor after X-ray excitation, the detective quantum efficiency (DQE), expressing the signal-to-noise ratio (SNR) transfer efficiency, and the information capacity were experimentally determined. The method was based on light flux and modulation transfer function (MTF) measurements and was used to assess the imaging performance of the Zn2SiO4:Mn phosphor. The latter was employed in the form of laboratory prepared phosphor layers (test screens). Results showed that high values for optical signal emission and DQE were obtained for medium thickness phosphor layers (56 and 89 mg/cm2) at 20 kVp X-ray tube voltage. The information capacity was found to decrease continuously with phosphor coating weight.

Biophysical Phenomena↗
PubMed1999

A method for determining the information capacity of x-ray imaging scintillator detectors by means of luminescence and modulation transfer function measurements.

A method to determine the information capacity of x-ray phosphor screens used in the detectors of medical imaging systems is described. Information capacity was determined via x-ray luminescence efficiency (XLE), modulation transfer function (MTF) and emission spectrum measurements. The method was applied to laboratory prepared screens from commonly employed phosphor materials. The screen coating weight varied from 50 mg cm-2 to 140 mg cm-2. Results indicated that information capacity decreased with screen coating thickness but also depended on intrinsic phosphor properties (density, effective atomic number, intrinsic conversion efficiency, light wavelength). The Gd2O2S:Tb phosphor, exhibiting high density and effective atomic number, was found to be superior to La2O2S:Tb and Y2O2S:Tb.

Electronic Data Processing↗