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Cervical cancer is one of the deadliest cancer known and is also a key research area in image processing. The main problem with this cancer is that it cannot be detected as it doesn't throw any symptoms until the final stages. This is attributed to the cancer itself and also to the lack of pathologists available to screen the cancer. Here we have proposed a(More)
Cervical cancer is one of the deadliest cancers that occur in women and the only way it could be curtailed is through an automated system. The sense of touch yields more information than visual and other senses. Here we have tried to exploit this concept by analyzing the textural features of cervical cyto images. The Nuclei of a Cervical cyto image possess(More)
Cervical cyto images have found keen interest among research enthusiasts in the recent past, not only because of its killer reputation but also due to the diverse challenging unsolved problem it possess. Cervical cancer like all other cancer develops through various stages before it actually causes potential harm. These stages can be detected through visual(More)
OBJECTIVE The purpose of this study was to evaluate an improved oriented speckle reducing anisotropic diffusion (IADF) filter that suppress the speckle noise from ultrasound B-mode images and shows better result than previous filters such as anisotropic diffusion, wavelet denoising and local statistics. METHODS The clinical ultrasound images of the cervix(More)
The paper proposes an efficient quad-tree based filtering algorithm for the restoration of impulse corrupted digital images. The quad-tree decomposition stage facilitates pixel classification in the impulse detection phase and minimizes miss-classification of signals as impulses by clearly distinguishing the high frequency image details from impulse(More)
The paper proposes a 2D impulse filtering algorithm for the restoration of impulse corrupted digital images. The algorithm incorporates a quad-tree decomposition stage to facilitate pixel classification in the impulse detection phase and an efficient adaptive filtering scheme in the restoration phase. The impulse detection scheme of the algorithm avoids(More)
The paper proposes a 2D impulse filtering algorithm for the restoration of salt & pepper impulse corrupted digital images. The algorithm incorporates a hard-C means clustering stage to facilitate pixel classification in the impulse detection phase and an efficient adaptive filtering scheme in the restoration phase. The impulse detection scheme of the(More)
Our main goal in this paper is to produce a method for the automated segmentation of an abnormality in a medical image, including acquiring first image data representative of the medical image; locating a suspicious site at which the abnormality may exist; establishing a selection point within the suspicious site; and preprocessing the suspicious site with(More)
A new impulse noise removal algorithm which exhibits improved performance in noise removal by addressing the limitations of the algorithms proposed by K.S.Srinivasan et. al.[18] and Madhu.et. al.[19] is proposed. The signal restoration scheme of the proposed filter adapts to the varied impulse noise ratios while determining an appropriate signal restorer(More)
The paper puts forward a new filtering algorithm for the restoration of digital images corrupted by impulse noise. The proposed filter includes a Hard-C means clustering stage in the impulse detection phase to facilitate pixel classification and an adaptive impulse filtering scheme in the restoration phase. The impulse detection phase avoids(More)
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