Biomedical subjects

George K Matsopoulos

Publications and source records attributed to George K Matsopoulos.

11 recordsLinked to original sources

PubMed2006

Image registration based on lifting process: an application to digital subtraction radiography.

In this paper, a digital subtraction radiology scheme is presented based on a new method for the automatic registration of dental radiographs acquired with or without rigorous a priori standardization. The scheme is comprised of an automatic registration method and a subtraction process. The proposed registration method can be considered as an object-based registration method without imposing the prerequisite of image segmentation in order to detect the boundary of the objects of interest or the automatic detection of matching landmarks. This is achieved by augmenting the dimensionality of the problem from two-dimensional gray-level matching to three-dimensional surface matching using the process of lifting in combination with a surface-matching technique. The pseudo three-dimensional affine transformation that matches the lifted images incorporates advantageous characteristics including spatial alignment of the surfaces, anisotropic correction of brightness/contrast differences, and stable convergence of the similarity function to its optimal value. The performance of the proposed automatic registration method is assessed against a manual method based on the projective transformation. The qualitative and quantitative assessments of the experiments have shown advantageous performance of the proposed automatic registration method against the manual one. Finally, the proposed registration method has been further improved in terms of execution time by the implementation of a surface decimation process.

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PubMed2004

Thoracic non-rigid registration combining self-organizing maps and radial basis functions.

An automatic three-dimensional non-rigid registration scheme is proposed in this paper and applied to thoracic computed tomography (CT) data of patients with stage III non-small cell lung cancer (NSCLC). According to the registration scheme, initially anatomical set of points such as the vertebral spine, the ribs, and shoulder blades are automatically segmented slice by slice from the two CT scans of the same patient in order to serve as interpolant points. Based on these extracted features, a rigid-body transformation is then applied to provide a pre-registration of the data. To establish correspondence between the feature points, the novel application of the self-organizing maps (SOMs) is adopted. In particular, the automatic correspondence of the interpolant points is based on the initialization of the Kohonen neural network model capable to identify 500 corresponding pairs of points approximately in the two CT sets. Then, radial basis functions (RBFs) using the shifted log function is subsequently employed for elastic warping of the image volume, using the correspondence between the interpolant points, as obtained in the previous phase. Quantitative and qualitative results are also presented to validate the performance of the proposed elastic registration scheme resulting in an alignment error of 6 mm, on average, over 15 CT paired datasets. Finally, changes of the tumor volume in respect to each reference dataset are estimated for all patients, which indicate inspiration and/or movement of the patient during acquisition of the data. Thus, the practical implementation of this scheme could provide estimations of lung tumor volumes during radiotherapy treatment planning.

Adult↗

PubMed2004

Registration of electronic portal images for patient set-up verification.

Images acquired from an electronic portal imaging device are aligned with digitally reconstructed radiographs (DRRs) or other portal images to verify patient positioning during radiation therapy. Most of the currently available computer aided registration methods are based on the manual placement of corresponding landmarks. The purpose of the paper is twofold: (a) the establishment of a methodology for patient set-up verification during radiotherapy based on the registration of electronic portal images, and (b) the evaluation of the proposed methodology in a clinical environment. The estimation of set-up errors, using the proposed methodology, can be accomplished by matching the portal image of the current fraction of the treatment with the portal image of the baseline treatment (reference portal image) using a nearly automated technique. The proposed registration method is tested on a number of phantom data as well as on data from four patients. The phantom data included portal images that corresponded to various positions of the phantom on the treatment couch. For each patient, a set of 30 portal images was used. For the phantom data (for both transverse and lateral portal images), the maximum absolute deviations of the translational shifts were within 1.5 mm, whereas the in-plane rotation angle error was less than 0.5 degrees. The two-way Anova revealed no statistical significant variability both within observer and between-observer measurements (P > 0.05). For the patient data, the mean values obtained with manual and the proposed registration methods were within 0.5 mm. In conclusion, the proposed registration method has been incorporated within a system, called ESTERR-PRO. Its image registration capability achieves high accuracy and both intra- and inter-user reproducibility. The system is fully operational within the Radiotherapy Department of 'HYGEIA' Hospital in Athens and it could be easily installed in any other clinical environment since it requires standardized hardware specifications and minimal human intervention.

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PubMed2004

MITIS: a WWW-based medical system for managing and processing gynecological-obstetrical-radiological data.

In this paper a World Wide Web (WWW)-based medical system, called MITIS, is designed and developed for the management and processing of obstetrical, gynecological and radiological medical data. The system records all the necessary medical information in terms of patient data, examinations, and operations and provides the user-expert with advanced image processing tools for the manipulation, processing and storage of ultrasound and mammographic images. The system can be installed in a hospital's Local Area Network (LAN) where it can access picture archival and communication systems (PACS) servers (if available), or any other server within the radiology department, for image archiving and retrieval, based on the digital imaging and communication in medicine (DICOM) 3.0 protocol, over TCP/IP and also it is accessible to external physicians via the hospital's Internet connection. MITIS is composed as a set of independent WWW modules (ISAPI server extension dlls) and a Win32 application (COM+ server) for mammography image processing and evaluation.

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PubMed2004

Multimodal registration of retinal images using self organizing maps.

In this paper, an automatic method for registering multimodal retinal images is presented. The method consists of three steps: the vessel centerline detection and extraction of bifurcation points only in the reference image, the automatic correspondence of bifurcation points in the two images using a novel implementation of the self organizing maps and the extraction of the parameters of the affine transform using the previously obtained correspondences. The proposed registration algorithm was tested on 24 multimodal retinal pairs and the obtained results show an advantageous performance in terms of accuracy with respect to the manual registration.

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PubMed2003

Do atypical antipsychotics fail to exert cognitive sparing effects?

The aim of the study was to investigate patterns of the P600 component of event-related potentials (ERPs) elicited during a working memory test in 16 male schizophrenic patients experiencing auditory hallucinations before and after treatment with clozapine and olanzapine, and 13 male normal subjects matched for age and educational level. Before treatment, patients showed significantly reduced P600 amplitudes on the right parietal region compared with controls, and when in remission also showed significantly reduced P600 amplitudes located on the right parietal and temporofrontal areas, compared both to themselves before treatment and to normal controls. The patient's memory performance before and after treatment remained significantly lower than that of healthy controls. These findings may indicate that auditory hallucinations in schizophrenia are associated with impaired synchronization of the processes related to target detection, as reflected by the P600. The present study also casts doubts regarding the cognitive sparing effect of atypical antipsychotics, despite the fact that they mediate symptom improvement.

Adult↗

PubMed2003

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier.

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Algorithms↗

PubMed2003

CT-MRI automatic surface-based registration schemes combining global and local optimization techniques.

Medical image registration is commonly required in order to combine the complementary information provided by different medical imaging modalities. In this paper, a new automatic registration scheme is proposed to register 3-D CT-MR head images and is currently tested on a clinical environment. The proposed scheme, after the preprocessing and the outer surface extraction of the data, is based on the use the rigid transformation method, in conjunction with a combination of global and local optimization techniques. Analytically, the paper exploits the optimization efficiency of three widely used optimization techniques, in obtaining the parameters of the rigid transformation model: the Downhill Simplex Method, the Genetic Algorithms and the Simulated Annealing. These optimization techniques are further combined by the sequential application of the Powell optimization method in order to refine the registration and increase its accuracy. A comparative study involving these optimization techniques in conjunction with the rigid transformation, and two other methods, the ICP and the manual methods, is also presented, for a sufficient number of clinical CT-MR brain images. Finally, quantitative and qualitative results are also presented to validate the performance of these automatic surface-based registration schemes, in terms of consistency and accuracy. Throughout of this study, the automatic registration scheme comprising of the rigid transformation in conjunction with the Simulated Annealing method sequentially combined with the Powell method has been performed superior regarding all the other compared registration schemes.

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PubMed2002

Fractal dimension estimation of carotid atherosclerotic plaques from B-mode ultrasound: a pilot study.

In this paper, a pilot study regarding carotid atherosclerotic plaque instability using B-mode ultrasound (US) images was carried out. The fractal dimension of plaques obtained from ten symptomatic subjects (i.e., subjects having experienced neurological symptoms) as well as from nine asymptomatic subjects, was estimated using a novel method, called the kth nearest neighbour (KNN) method. The results indicated a significant difference, as per the fractal dimension, between the two groups, providing a significantly lower value for the asymptomatic group. Moreover, the phase of the cardiac cycle (systole/diastole) during which the fractal dimension was estimated had no systematic effect on the calculations. The fractal dimension of the plaques was also estimated using a well-known method, namely the box-counting (BC) method. No significant differences between the two groups, as per the fractal dimension, were observed using the BC method. The presented pilot study suggests that the fractal dimension, estimated by the proposed method, could be used as a single determinant for the discrimination of symptomatic and asymptomatic subjects.

Aged↗

PubMed2002

Use of image processing techniques to assess effect of disodium pamidronate in conjunction with radiotherapy in patients with bone metastases.

The aim of this study was radiographically to monitor the effect of disodium pamidronate on metastatic bone disease, using image-processing techniques. Eighteen patients with osteolytic metastases from breast cancer received an intravenous infusion of 180 mg disodium pamidronate every 4 weeks for a period of 6 months. The first session of intravenous infusions was given concurrently with external beam radiotherapy with a 6 MV linear accelerator (total dose 30 Gy in 10 fractions). Radiographs of osteolytic lesions were obtained at every session of the treatment, retaining the same settings for each modality. The analysis of the attributes of the images was based on measuring the first-order statistics of the gray-level histogram in terms of mean value (MVGLH) and energy (EGLH). The measurements showed significant differences for MVGLH and EGLH values (p < 0.05, Wilcoxon test). Analytically, there was an 11.08% (95% CI = 10.21, 11.93) mean reduction of EGLH and an 11.63% (95% CI = 10.96, 12.29) mean increase of MVGLH of the x-ray images, before and after the combined treatment protocol. The changes in the image-processing indices were also highly correlated with the reduction of the patient's pain score. These findings indicate an important increase in bone mass and bone formation, which the radiologists found difficult to identify visually.

Adult↗

PubMed2002

A comparative study of surface- and volume-based techniques for the automatic registration between CT and SPECT brain images.

Image registration of multimodality images is an essential task in numerous applications in three-dimensional medical image processing. Medical diagnosis can benefit from the complementary information in different modality images. Surface-based registration techniques, while still widely used, were succeeded by volume-based registration algorithms that appear to be theoretically advantageous in terms of reliability and accuracy. Several applications of such algorithms for the registration of CT-MRI, CT-PET, MRI-PET, and SPECT-MRI images have emerged in the literature, using local optimization techniques for the matching of images. Our purpose in this work is the development of automatic techniques for the registration of real CT and SPECT images, based on either surface- or volume-based algorithms. Optimization is achieved using genetic algorithms that are known for their robustness. The two techniques are compared against a well-established method, the Iterative Closest Point-ICP. The correlation coefficient was employed as an independent measure of spatial match, to produce unbiased results. The repeated measures ANOVA indicates the significant impact of the choice of registration method on the magnitude of the correlation (F = 4.968, p = 0.0396). The volume-based method achieves an average correlation coefficient value of 0.454 with a standard deviation of 0.0395, as opposed to an average of 0.380 with a standard deviation of 0.0603 achieved by the surface-based method and an average of 0.396 with a standard deviation equal to 0.0353 achieved by ICP. The volume-based technique performs significantly better compared to both ICP (p<0.05, Neuman Keuls test) and the surface-based technique (p<0.05, Neuman-Keuls test). Surface-based registration and ICP do not differ significantly in performance.

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