ATD: a multiplatform for semiautomatic 3-D detection of kidneys and their pathology in real time

This research presents a novel multi-functional system for medical Imaging-enabled Assistive Diagnosis (IAD). Although the IAD demonstrator has focused on abdominal images and supports the clinical diagnosis of kidneys using CT/MRI imaging, it can be adapted to work on image delineation, annotation and 3D real-size volumetric modelling of other organ structures such as the brain, spine, etc. The IAD provides advanced real-time 3D visualisation and measurements with fully automated functionalities as developed in two stages. In the first stage, via the clinically driven user interface, specialist clinicians use CT/MRI imaging datasets to accurately delineate and annotate the kidneys and their possible abnormalities, thus creating “3D Golden Standard Models”. Based on these models, in the second stage, clinical support staff i.e. medical technicians interactively define model-based rules and parameters for the integrated “Automatic Recognition Framework” to achieve results which are closest to that of the clinicians. These specific rules and parameters are stored in “Templates” and can later be used by any clinician to automatically identify organ structures i.e. kidneys and their possible abnormalities. The system also supports the transmission of these “Templates” to another expert for a second opinion. A 3D model of the body, the organs and their possible pathology with real metrics is also integrated. The automatic functionality was tested on eleven MRI datasets (comprising of 286 images) and the 3D models were validated by comparing them with the metrics from the corresponding “3D Golden Standard Models”. The system provides metrics for the evaluation of the results, in terms of Accuracy, Precision, Sensitivity, Specificity and Dice Similarity Coefficient (DSC) so as to enable benchmarking of its performance. The first IAD prototype has produced promising results as its performance accuracy based on the most widely deployed evaluation metric, DSC, yields 97% for the recognition of kidneys and 96% for their abnormalities; whilst across all the above evaluation metrics its performance ranges between 96% and 100%. Further development of the IAD system is in progress to extend and evaluate its clinical diagnostic support capability through development and integration of additional algorithms to offer fully computer-aided identification of other organs and their abnormalities based on CT/MRI/Ultra-sound Imaging.

A malware detection system inspired on the human immune system

Malicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.

A subpixel edge detector applied to aortic dissection detection

[EN] The aortic dissection is a disease that can cause a deadly situation, even with a correct treatment. It consists in a rupture of a layer of the aortic artery wall, causing a blood flow inside this rupture, called dissection. The aim of this paper is to contribute to its diagnosis, detecting the dissection edges inside the aorta. A subpixel accuracy edge detector based on the hypothesis of partial volume effect is used, where the intensity of an edge pixel is the sum of the contribution of each color weighted by its relative area inside the pixel. The method uses a floating window centred on the edge pixel and computes the edge features. The accuracy of our method is evaluated on synthetic images of different hickness and noise levels, obtaining an edge detection with a maximal mean error lower than 16 percent of a pixel.

The Equidistant Method - a novel hip joint simulation algorithm for detection of femoroacetabular impingement

A novel computerized algorithm for hip joint motion simulation and collision detection, called the Equidistant Method, has been developed. This was compared to three pre-existing methods having different properties regarding definition of the hip joint center and behavior after collision detection. It was proposed that the Equidistant Method would be most accurate in detecting the location and extent of femoroacetabular impingement.

Automated detection of fiducial screws from CT/DVT volume data for image-guided ENT surgery

This paper presents an automated solution for precise detection of fiducial screws from three-dimensional (3D) Computerized Tomography (CT)/Digital Volume Tomography (DVT) data for image-guided ENT surgery. Unlike previously published solutions, we regard the detection of the fiducial screws from the CT/DVT volume data as a pose estimation problem. We thus developed a model-based solution. Starting from a user-supplied initialization, our solution detects the fiducial screws by iteratively matching a computer aided design (CAD) model of the fiducial screw to features extracted from the CT/DVT data. We validated our solution on one conventional CT dataset and on five DVT volume datasets, resulting in a total detection of 24 fiducial screws. Our experimental results indicate that the proposed solution achieves much higher reproducibility and precision than the manual detection. Further comparison shows that the proposed solution produces better results on the DVT dataset than on the conventional CT dataset.

Comparison of multispectral wide-field optical imaging modalities to maximize image contrast for objective discrimination of oral neoplasia

Multispectral widefield optical imaging has the potential to improve early detection of oral cancer. The appropriate selection of illumination and collection conditions is required to maximize diagnostic ability. The goals of this study were to (i) evaluate image contrast between oral cancer/precancer and non-neoplastic mucosa for a variety of imaging modalities and illumination/collection conditions, and (ii) use classification algorithms to evaluate and compare the diagnostic utility of these modalities to discriminate cancers and precancers from normal tissue. Narrowband reflectance, autofluorescence, and polarized reflectance images were obtained from 61 patients and 11 normal volunteers. Image contrast was compared to identify modalities and conditions yielding greatest contrast. Image features were extracted and used to train and evaluate classification algorithms to discriminate tissue as non-neoplastic, dysplastic, or cancer; results were compared to histologic diagnosis. Autofluorescence imaging at 405-nm excitation provided the greatest image contrast, and the ratio of red-to-green fluorescence intensity computed from these images provided the best classification of dysplasia/cancer versus non-neoplastic tissue. A sensitivity of 100% and a specificity of 85% were achieved in the validation set. Multispectral widefield images can accurately distinguish neoplastic and non-neoplastic tissue; however, the ability to separate precancerous lesions from cancers with this technique was limited. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3516593]

Quantitative three-dimensional power Doppler angiography: a flow-free phantom experiment to evaluate the relationship between color gain, depth and signal artifact

Objectives To evaluate the presence of false flow three-dimensional (3D) power Doppler signals in `flow-free` models. Methods 3D power Doppler datasets were acquired from three different flow-free phantoms (muscle, air and water) with two different transducers and Virtual Organ Computer-aided AnaLysis was used to generate a sphere that was serially applied through the 3D dataset. The vascularization flow index was used to compare artifactual signals at different depths (from 0 to 6 cm) within the different phantoms and at different gain and pulse repetition frequency (PR F) settings. Results Artifactual Doppler signals were seen in all phantoms despite these being flow-free. The pattern was very similar and the degree of artifact appeared to be dependent on the gain and distance from the transducer. False signals were more evident in the far field and increased as the gain was increased, with false signals first appearing with a gain of 1 dB in the air and muscle phantoms. False signals were seen at a lower gain with the water phantom (-15 dB) and these were associated with vertical lines of Doppler artifact that were related to PRF, and disappeared when reflections were attenuated. Conclusions Artifactual Doppler signals are seen in flow-free phantoms and are related to the gain settings and the distance from the transducer. In the in-vivo situation, the lowest gain settings that allow the detection of blood flow and adequate definition of vessel architecture should be used, which invariably means using a setting near or below the middle of the range available. Additionally, observers should be aware of vertical lines when evaluating cystic or liquid-containing structures. Copyright (C) 2010 ISUOC. Published by John Wiley & Sons, Ltd.

Avaliação da caracterização de lesões em mamografia com recurso a sistemas CAD (Diagnóstico Assistido por Computador)

Mestrado em Radiações Aplicadas às Tecnologias da Saúde. Área de especialização: Imagem Digital com Radiação X.

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Abstracting qualitative information for process supervision

Supervisory systems evolution makes the obtaining of significant information from processes more important in the way that the supervision systems' particular tasks are simplified. So, having signal treatment tools capable of obtaining elaborate information from the process data is important. In this paper, a tool that obtains qualitative data about the trends and oscillation of signals is presented. An application of this tool is presented as well. In this case, the tool, implemented in a computer-aided control systems design (CACSD) environment, is used in order to give to an expert system for fault detection in a laboratory plant

Variability of ascending aorta diameter measurements as assessed with electrocardiography-gated multidetector computerized tomography and computer assisted diagnosis software.

Recently, morphometric measurements of the ascending aorta have been done with ECG-gated multidector computerized tomography (MDCT) to help the development of future novel transcatheter therapies (TCT); nevertheless, the variability of such measurements remains unknown. Thirty patients referred for ECG-gated CT thoracic angiography were evaluated. Continuous reformations of the ascending aorta, perpendicular to the centerline, were obtained automatically with a commercially available computer aided diagnosis (CAD). Then measurements of the maximal diameter were done with the CAD and manually by two observers (separately). Measurements were repeated one month later. The Bland-Altman method, Spearman coefficients, and a Wilcoxon signed-rank test were used to evaluate the variability, the correlation, and the differences between observers. The interobserver variability for maximal diameter between the two observers was up to 1.2 mm with limits of agreement [-1.5, +0.9] mm; whereas the intraobserver limits were [-1.2, +1.0] mm for the first observer and [-0.8, +0.8] mm for the second observer. The intraobserver CAD variability was 0.8 mm. The correlation was good between observers and the CAD (0.980-0.986); however, significant differences do exist (P<0.001). The maximum variability observed was 1.2 mm and should be considered in reports of measurements of the ascending aorta. The CAD is as reproducible as an experienced reader.

Investigation of high-resolution functional magnetic resonance imaging by means of surface and array radiofrequency coils at 7 T.

In this investigation, high-resolution, 1x1x1-mm(3) functional magnetic resonance imaging (fMRI) at 7 T is performed using a multichannel array head coil and a surface coil approach. Scan geometry was optimized for each coil separately to exploit the strengths of both coils. Acquisitions with the surface coil focused on partial brain coverage, while whole-brain coverage fMRI experiments were performed with the array head coil. BOLD sensitivity in the occipital lobe was found to be higher with the surface coil than with the head array, suggesting that restriction of signal detection to the area of interest may be beneficial for localized activation studies. Performing independent component analysis (ICA) decomposition of the fMRI data, we consistently detected BOLD signal changes and resting state networks. In the surface coil data, a small negative BOLD response could be detected in these resting state network areas. Also in the data acquired with the surface coil, two distinct components of the positive BOLD signal were consistently observed. These two components were tentatively assigned to tissue and venous signal changes.

O6-Methylguanine-DNA methyltransferase protein expression by immunohistochemistry in brain and non-brain systemic tumours: systematic review and meta-analysis of correlation with methylation-specific polymerase chain reaction

Background: The DNA repair protein O6-Methylguanine-DNA methyltransferase (MGMT) confers resistance to alkylating agents. Several methods have been applied to its analysis, with methylation-specific polymerase chain reaction (MSP) the most commonly used for promoter methylation study, while immunohistochemistry (IHC) has become the most frequently used for the detection of MGMT protein expression. Agreement on the best and most reliable technique for evaluating MGMT status remains unsettled. The aim of this study was to perform a systematic review and meta-analysis of the correlation between IHC and MSP. Methods A computer-aided search of MEDLINE (1950-October 2009), EBSCO (1966-October 2009) and EMBASE (1974-October 2009) was performed for relevant publications. Studies meeting inclusion criteria were those comparing MGMT protein expression by IHC with MGMT promoter methylation by MSP in the same cohort of patients. Methodological quality was assessed by using the QUADAS and STARD instruments. Previously published guidelines were followed for meta-analysis performance. Results Of 254 studies identified as eligible for full-text review, 52 (20.5%) met the inclusion criteria. The review showed that results of MGMT protein expression by IHC are not in close agreement with those obtained with MSP. Moreover, type of tumour (primary brain tumour vs others) was an independent covariate of accuracy estimates in the meta-regression analysis beyond the cut-off value. Conclusions Protein expression assessed by IHC alone fails to reflect the promoter methylation status of MGMT. Thus, in attempts at clinical diagnosis the two methods seem to select different groups of patients and should not be used interchangeably.