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Heart Beat Rate calculation has traditionally been conducted using specialized hardware most commonly in the form of pulse oximeters or Electrocardiogram devices. Even though these methods offer high reliability, they require the users to have special sensor to measure their heart rate. In this paper we propose a system capable of estimating the heart beat rate using just a camera from a commercially...
This paper investigates the applicability of multilevel macroscopic models for simulating solid tumor growth in the invasive glioblastoma multiforme (GBM) case. The continuum case approach tumor model based on the diffusion reaction equation is evaluated on a pre-segmented tomographic atlas where all tissue properties are known a priori. The atlas is further registered on a real clinical case where...
This paper presents the work of our group concerning cancer image analysis and modeling. The adopted strategy aims to build a complete system for analysis and visualization of DICOM tomographic data, offering a variety of annotation or automatic segmentation tools as well as tools for tumor growth simulation and visualization.
Several mathematical models have been developed to express glioma growth behavior. The most successful models have used the diffusion-reaction equation, with the most recent ones taking into account spatial heterogeneity and anisotropy. However, to the best of our knowledge, there hasn't been any work studying in detail the mathematical solution and implementation of the 3D diffusion model, addressing...
This paper describes a flexible and easy-to-use annotation platform (GUI) for quick and precise identification and delineation of tumors in medical images. The design of the platform is clinically driven in order to ensure that the clinician can efficiently and intuitively annotate large number of 3D tomographic datasets. Both manual and well-known semiautomatic segmentation techniques are available...
Glioma is the most aggressive type of brain cancer. Several mathematical models have been developed towards identifying the mechanism of tumor growth. The most successful models have used variations of the diffusion-reaction equation, with the recent ones taking into account brain tissue heterogeneity and anisotropy. However, to the best of our knowledge, there hasn't been any work studying in detail...
Tomographic reconstruction of fluorescence optical projection tomography (OPT) data is usually performed using the standard filtered back projection (FBP) algorithm. However, there are several physical aspects of fluorescence OPT that pose major challenges for the FBP algorithm. These include blurring, and the fact that for an isotropically emitting point source (or fluorophore), the power received...
Optical Projection Tomography (OPT) suffers from additive CCD detector noise. This paper investigates the nature of the CCD detector noise for an OPT setup. The CCD detector noise is found to be described well by an intensity dependent zero-mean Gaussian distribution. A method of reducing the effect of noise in fluorescence OPT reconstructions is discussed. The results of the noise reduction are demonstrated...
DNA microarrays have demonstrated an excellent potential in correlating specific gene expression profiles to specific conditions. However, they are affected by inherent noise. This paper presents a two-stage approach for noise removal that processes the additive and the multiplicative noise component. The proposed approach first decomposes the signal by a multiresolution transform and then accounts...
Statistical shape analysis techniques commonly employed in the medical imaging community, such as active shape models or active appearance models, rely on principal component analysis (PCA) to decompose shape variability into a reduced set of interpretable components. In this paper we propose principal factor analysis (PFA) as an alternative and complementary tool to PCA providing a decomposition...
High-throughput gene expression is an important aspect of modern post-genomic research. Microarray technology is the driving force of this revolution, a technology that allows the simultaneous monitoring of expression for thousands of genes. The need for accurate and reproducible research has driven the development of robust analysis frameworks for maximizing the information content of biological...
High-throughput gene expression is an important aspect of modern post-genomic research. Microarray technology is the driving force of this revolution, a technology that allows the simultaneous monitoring of expression for thousands of genes. The need for accurate and reproducible research has driven the development of robust analysis frameworks for maximizing the information content of biological...
High-throughput gene expression is an important aspect of modern post-genomic research. Microarray technology is the driving force of this revolution, a technology that allows the simultaneous monitoring of expression for thousands of genes. The need for accurate and reproducible research has driven the development of robust analysis frameworks for maximizing the information content of biological...
This paper presents a novel platform for image retrieval based on a two-level architecture inspired from human cognitive mechanisms. These two levels provide both generic similarity and semantic information related to special characteristics. Although the proposed architecture can be customized for any content-based image retrieval application, our work is focused on medical images and more specifically...
Intelligent management of medical data is an important field of research in clinical information and decision support systems. Such systems are finding increasing use in the management of patients known to have, or suspected of having, breast cancer. Different types of breast-tissue patterns convey semantic information which is reported by the radiologist when reading mammograms. In this paper, a...
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