RESUMO
This paper describes the methodology and the evaluation of a 3D skeletonization algorithm applied on brain vascular structure. This method is based on the application of the minimum cost-spanning tree using Dijkstra's algorithm and seems well appropriate to tubular objects. We briefly describe the different steps, from the segmentation to the skeleton analysis. Besides, we propose an original evaluation scheme of the method based on digital phantom and clinical data. The final aim of this work is to provide a symbolic description framework applied to cerebro-vascular structures.
Assuntos
Encéfalo/irrigação sanguínea , Eletroencefalografia/métodos , Imageamento Tridimensional/métodos , Algoritmos , Circulação Cerebrovascular , Humanos , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Reconhecimento Automatizado de Padrão/métodos , Imagens de Fantasmas , Linguagens de Programação , SoftwareRESUMO
Single photon emission computed tomography (SPECT) is an accurate imaging method for the diagnosis of refractory partial epilepsy. Two scans are carried out: interictal and ictal. The interest of this method is to provide an image in the ictal period, which allows hyperperfused areas linked to the seizure to be localized. The epileptic foci localization is improved by subtracting the two acquisitions (subtracted ictal SPECT: SIS). In some cases, the SIS method is not effective and does not isolate the seizure foci. In this article, we investigate a new method based on texture analysis using fractal geometry features. Fractal geometry features were extracted from each scan in order to quantify the heterogeneity change resulting from the hyperperfusion. A support vector machine (SVM) classification algorithm was used to classify the voxels into two classes: focal and healthy. Quantitative evaluation was performed on simulated images and clinical images from 22 patients with temporal lobe epilepsy. Results on both experiments showed that the proposed method is more specific and more sensitive than the SIS method.
Assuntos
Algoritmos , Epilepsia do Lobo Temporal/diagnóstico por imagem , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Reconhecimento Automatizado de Padrão/métodos , Tomografia Computadorizada de Emissão de Fóton Único/métodos , Inteligência Artificial , Fractais , Humanos , Aumento da Imagem/métodos , Imagens de Fantasmas , Reprodutibilidade dos Testes , Sensibilidade e EspecificidadeRESUMO
One of the imaging modalities used for the diagnosis of epilepsy is SPECT (Single-Photon Emission Computed Tomography). Ictal and interictal images are registered to MR images (SISCOM (Substracted Ictal Spect COregistred to MR) to delineate the sources. However, in some cases and for many reasons, the used method does not lead to precise delimitation of epileptic fit sources. In this case, works have been investigated on group's studies or in combining others modalities like EEG (Electroencephalography). This study investigates the possibility of using a mathematic model for the image texture to detect the changes on SPECT images. Beyond encouraging preliminary results concerning the multifractal analysis to distinguish volunteers and epileptic patients, our aim was to detect sources by the singularity spectrum compute. The experiment is divided into two phases. First, we developed a 3D method for the singularity spectrum compute. In the test phase, we applied this multifractal spectrum to the sources detection on SPECT images. The results obtained on a base of seven patients show that the proposed method is encouraging. Indeed, the detections of epileptic fit sources obtained were in agree with the expert diagnostic.
Assuntos
Encéfalo/patologia , Epilepsia/diagnóstico , Epilepsia/patologia , Imageamento Tridimensional/métodos , Tomografia Computadorizada de Emissão de Fóton Único/métodos , Algoritmos , Gráficos por Computador , Fractais , Humanos , Processamento de Imagem Assistida por Computador/métodos , Modelos Teóricos , Doenças do Sistema Nervoso/diagnóstico , Doenças do Sistema Nervoso/patologia , Valores de Referência , Reprodutibilidade dos TestesRESUMO
This paper describes a method to register ultrasound images (US) to pre-treatment images. The aim of the work is the information transfer between the pre-treatment imaging modality (MR or CT) and the intra-treatment imaging (US). Ultrasound images are spatially tracked by a stereo-vision system and the prostate boundaries are automatically extracted using a method that combines morphological and adaptive speckle suppression and a priori knowledge. MR/CT images are merged to construct a volume of pelvis using fuzzy logic algorithm and an MPR virtual slice corresponding to the orientation of the US image is generated from the volume. The prostate is segmented from the slice by a model-based method and rigidly registered by ICP algorithm to the US contour. Preliminary experiences gave satisfactory results with short computing time.