Hamid Soltanian-Zadeh

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This paper introduces a new feature vector for shape-based image indexing and retrieval. This feature classi5es image edges based on two factors: their orientations and correlation between neighboring edges. Hence it includes information of continuous edges and lines of images and describes major shape properties of images. This scheme is e8ective and(More)
This paper presents a new approach to rotation invariant texture classification. The proposed approach benefits from the fact that most of the texture patterns either have directionality (anisotropic textures) or are not with a specific direction (isotropic textures). The wavelet energy features of the directional textures change significantly when the(More)
Histological grading of pathological images is used to determine level of malignancy of cancerous tissues. This is a very important task in prostate cancer prognosis, since it is used for treatment planning. If infection of cancer is not rejected by non-invasive diagnostic techniques like magnetic resonance imaging, computed tomography scan, and ultrasound,(More)
We present an evaluation and comparison of the performance of four di5erent texture and shape feature extraction methods for classi(cation of benign and malignant microcalci(cations in mammograms. For 103 regions containing microcalci(cation clusters, texture and shape features were extracted using four approaches: conventional shape quanti(ers;(More)
In an effort to elucidate the molecular mechanisms underlying cerebral vascular alteration after stroke, the authors measured the spatial and temporal profiles of blood-brain barrier (BBB) leakage, angiogenesis, vascular endothelial growth factor (VEGF), associated receptors, and angiopoietins and receptors after embolic stroke in the rat. Two to four hours(More)
One of the most challenging problems of clustering is detecting the exact number of clusters in a dataset. Most of the previous methods, presented to solve this problem, estimate the number of clusters with model based algorithms, which are not able to detect all types of clusters and also face a problem in detecting coupled clusters in a dataset. In this(More)
BACKGROUND AND PURPOSE After stroke, brain tissue undergoes time-dependent heterogeneous histopathological change. These tissue alterations have MRI characteristics that allow segmentation of ischemic from nonischemic tissue. Moreover, MRI segmentation generates different zones within the lesion that may reflect heterogeneity of tissue damage. METHODS A(More)
We introduce a bottom-up model for integrating electroencephalography (EEG) or magnetoencephalography (MEG) with functional magnetic resonance imaging (fMRI). An extended neural mass model is proposed based on the physiological principles of cortical minicolumns and their connections. The fMRI signal is extracted from the proposed neural mass model by(More)
Recognition of iris based on Visible Light (VL) imaging is a difficult problem because of the light reflection from the cornea. Nonetheless, pigment melanin provides a rich feature source in VL, unavailable in Near-Infrared (NIR) imaging. This is due to biological spectroscopy of eumelanin, a chemical not stimulated in NIR. In this case, a plausible(More)
A new rotation-invariant texture-analysis technique using Radon and wavelet transforms is proposed. This technique utilizes the Radon transform to convert the rotation to translation and then applies a translation-invariant wavelet transform to the result to extract texture features. A k-nearest neighbors classifier is employed to classify texture patterns.(More)