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Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form.(More)
The inherent complexity and non-homogeneity of texture makes classification in medical image analysis a challenging task. In this paper, we propose a combined approach for meningioma subtype classification using subband texture (macro) features and micro-texture features. These are captured using the Adaptive Wavelet Packet Transform (ADWPT) and Local(More)
Computer aided diagnosis (CAD) is aimed at supporting the pathologists in their diagnosis. In this paper, we present an algorithm for texture-based classification of colon tissue patterns. In this method, a single band is selected from its hy-perspectral cube and spatial analysis is performed using circular local binary pattern (CLBP) features. A novel(More)
Diagnosis of recurrent miscarriage due to abnormally high number of uterine natural killer (uNK) cells has recently been made possible by a protocol devised by Quenby et al. Hum Reprod 2009;24(1):45-54. The diagnosis involves detection and counting of stromal and uNK cell nuclei in endometrial biopsy slides immunohistochemically stained with haematoxylin(More)
In this paper, we present a novel algorithm for restoration of noisy video sequences. A video sequence is first transformed into an optimal 3D wavelet domain using basis functions adapted to the contents of the sequence. Assuming that all the major spatiotemporal frequency phenomena present in the sequence produce high amplitude transform coefficients , a(More)
Image coding methods based on adaptive wavelet transforms and those employing zerotree quantization have been shown to be successful. We present a general zerotree structure for an arbitrary wavelet packet geometry in an image coding framework. A fast basis selection algorithm is developed; it uses a Markov chain based cost estimate of encoding the image(More)
The classification of normal and malginant colon tissue cells is crucial to the diagnosis of colon cancer in humans. Given the right set of feature vectors, Support Vector Machines (SVMs) have been shown to perform reasonably well for the classification [4, 13]. In this paper, we address the following question: how does the choice of a kernel function and(More)
UNLABELLED In this paper, we propose a statistical approach for mitosis detection in breast cancer histological images. The proposed algorithm models the pixel intensities in mitotic and non-mitotic regions by a Gamma-Gaussian mixture model (GGMM) and employs a context aware post-processing (CAPP) in order to reduce false positives. Experimental results(More)
Histopathology diagnosis is based on visual examination of the morphology of histological sections under a microscope. With the increasing popularity of digital slide scanners, decision support systems based on the analysis of digital pathology images are in high demand. However, computerized decision support systems are fraught with problems that stem from(More)