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Determining the blood flow patterns from medical images taken with a contrast agent is a problem situated at the congruency of multiple domains: medicine, image processing, mechanics and automatics. The outcome of such investigations can be used by clinicians in diagnosis and treatment of vascular diseases. In this paper we propose a method for automatic detection of a cerebral disease - the arterio-venous...
The paper presents some recent advances concerning a non-invasive microwave technique which is investigating living structures. A thermogram is plotted, obtained by microwave radiometry. Rigorous scientific studies have shown that the thermo-effect is accompanying growing tumors and atypical developing tissues. Early breast cancer structures are highlighted by this method, two cases being detected:...
An alternative method of diagnosing malignant lung nodules by their visual appearance rather than conventional growth rate is proposed. Spatial distribution of image intensities (or Hounsfield values) comprising the malignant nodule appearance is accurately modeled with a rotation invariant second-order Markov-Gibbs random field. Its neighborhood system and potentials are analytically learned from...
In this paper we propose using histogram intersection for mammographic image classification. First, we use the bag-of-words model for image representation, which captures the texture information by collecting local patch statistics. Then, we propose using normalized histogram intersection (HI) as a similarity measure with the K-nearest neighbor (KNN) classifier. Furthermore, by taking advantage of...
With the development of modern science, the goal of medical research is not limit to explore a type of disease but more accurate multi-subtypes of this disease. For example breast cancer can be divided into three different subtypes: BRCA1, BRCA2 and Sporadic. Previous work only focuses on distinguishing several pairs of tumors. However, the simultaneous distinguish across multiple disease types has...
In this paper, we are proposing a novel automated method to recognize centroblast (CB) cells from non-centroblast (non-CB) cells for computer-assisted evaluation of follicular lymphoma tissue samples. The method is based on training and testing of a quadratic discriminant analysis (QDA) classifier. The novel aspects of this method are the identification of the CB object with prior information, and...
One of the hallmarks of Alzheimer's disease (AD) is the loss of neurons in the brain. In many cases, the medical experts use MR (magnetic resonance) images to qualitatively measure the neuronal loss by the shrinkage (atrophy) of the structures-of-interest, or sometimes more easily by the enlargement of the fluid-filled structures, such as the ventricles. For quantitative analysis, volume is the common...
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