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Journals and Conferences
-This paper presents an overview of feature extraction methods for off-line recognition of segmented (isolated) characters. Selection of a feature extraction method is probably the single most important factor in achieving high recognition performance in character recognition systems. Different feature extraction methods are designed for different… (More)
This paper presents an evaluation of eleven locally adaptive binarization methods for gray scale images with low contrast, variable background intensity and noise. Niblack’s method with the addition of the postprocessing step of Yanowitz and Bruckstein’s method added performed the best and was also one of the fastest binarization methods.
AbstructA general model for multisource classification of remotely sensed data based on Markov Random Fields (MRF) is proposed. A specific model for fusion of optical images, synthetic aperture radar (SAR) images, and GIS (Geographic Information Systems) ground cover data is presented in detail and tested. The MRF model exploits spatial class dependencies… (More)
In this paper, White and Rohrer's \Integrated Function Algorithm" (1983) for binarization of gray level document images is improved. This is achieved by smoothing, a new print pixel identiication strategy, and a postprocessing step removing false print objects.
Bevacizumab, an antibody against vascular endothelial growth factor (VEGF), is a promising, yet controversial, drug in human glioblastoma treatment (GBM). Its effects on tumor burden, recurrence, and vascular physiology are unclear. We therefore determined the tumor response to bevacizumab at the phenotypic, physiological, and molecular level in a… (More)
Abstruct-We propose a new method for statistical classification of multisource data. The method is suited for land-use classification based on the fusion of remotely sensed images of the same scene captured at different dates from multiple sources. It incorporates u priori information about the likelihood of changes between the acquisition of the different… (More)
To study the feasibility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for assessment of tumour microvasculature in endometrial carcinoma patients, and to explore correlations with histological subtype, clinical course and microstructural characteristics based on apparent diffusion coefficient (ADC) values. Diffusion-weighted imaging… (More)
BACKGROUND Arterial input functions may differ between brain regions due to delay and dispersion effects in the vascular supply network. Unless corrected for, these differences may degrade quantitative estimations of cerebral blood flow in dynamic susceptibility contrast magnetic resonance perfusion imaging (DSC-MRI). PURPOSE To investigate in a healthy… (More)
The authors demonstrate an improved differentiation of the most common tissue types in the human brain and surrounding structures by quantitative validation using multispectral analysis of magnetic resonance images. This is made possible by a combination of a special training technique and an increase in the number of magnetic resonance channel images with… (More)