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Madian N.,KS Rangasamy College of Technology | Jayanthi K.B.,KS Rangasamy College of Technology | Suresh S.,Mediscan Systems
2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 | Year: 2015

Cytogenetics deals with the study of human chromosomes. This helps in detecting birth defects. Segmentation of overlapped chromosomes in metaphase images is very important in chromosome analysis. This becomes a complex task when more than one overlap occurs in the chromosomes mainly due to the non rigid nature of the chromosomes. This paper proposes an algorithm for identification of overlap zone which is the important step in segmentation of overlapping chromosomes without human intervention. Outer contour of the chromosomes is obtained including the overlapping zones. Then the curvature function is used to identify the concave and convex points. These concave points are used in finding the overlap zones. More than one overlap is identified correctly. G-band metaphase chromosome images are taken for analysis. The algorithm is robust. It is tested on more than 350 images with various number and degree of overlaps. The overall accuracy of the algorithm is 96%. © 2015 IEEE. Source


Hemalatha R.,Knowledge Institute of Technology | Santhiyakumari N.,Knowledge Institute of Technology | Suresh S.,Mediscan Systems
International Conference on Signal Processing and Communication Engineering Systems - Proceedings of SPACES 2015, in Association with IEEE | Year: 2015

In the decade of technological advancement, the image processing techniques has made it possible to save lives of several beings. The diagnosis of cardiovascular involved in complex procedures whereas the analysis of blood vessels carried out. The image segmentation technique is used to eliminate such complexities in Ultrasound carotid image diagnosis. In this paper the implementation of segmented intima-media interface of the common carotid artery image has been proposed in real time Virtex Field Programmable Gate Array. The intima-media interface has been extracted using threshold segmentation technique. The pre-processing step is used to remove speckles present in the ultrasound carotid image and the morphological techniques can be used in segmentation algorithm with the aid of Aphelion Dev software. The resulting image has been implemented in Virtex which provides minimum hardware resources and low power consumption and is desirable for real time medical applications and analysis. © 2015 IEEE. Source


Selvan S.,Anna University | Kavitha M.,Anna University | Shenbagadevi S.,Anna University | Suresh S.,Mediscan Systems
Journal of Computer Science | Year: 2010

Problem statement: Elastography is developed as a quantitative approach to imaging linear elastic properties of tissues to detect suspicious tumors. We propose an automatic feature extraction method in ultrasound elastography and echography for characterization of breast lesions. Approach: The proposed algorithm was tested on 40 pairs of biopsy proven ultrasound elastography and echography images of which 11 are cystic, 16 benign and 13 malignant lesions. Ultrasound elastography and echography images of breast tissue are acquired using Siemens (Acuston Antares) ultrasound scanner with a 7.3 MHz linear array transducer. The images were preprocessed and subjected to automatic threshold, resulting in binary images. The contours of a breast tumor from both echographic and elastographic images were segmented using level set method. Initially, six texture features of segmented lesions are computed from the two image types followed by computing three strain and two shape features using parameters from segmented lesions of both elastographic and echographic images. Results: These features were computed to assess their effectiveness at distinguishing benign, malignant and cystic lesions. It was found that the texture features extracted from benign and cystic lesions of an elastogram are more distinct than that of an ultrasound image .The strain and shape features of malignant lesions are distinct from that of benign lesions, but these features do not show much variation between benign and cystic lesions. Conclusion: As strain, shape and texture features are distinct for benign, malignant and cystic lesions, classification of breast lesions using these features is under implementation. © 2010 Science Publications. Source


Selvan S.,Anna University | Shenbagadevi S.,Anna University | Suresh S.,Mediscan Systems
Advances in Intelligent Systems and Computing | Year: 2015

Ultrasound (US) elastography, a new technique that images the elasticity of tissues, is now into the course of breast cancer diagnosis. The purpose of this study was to assess the diagnostic performance of a neural network using a combination of US elastography technique and US B-mode. A back-propagation neural network (BPN) is used to classify the breast masses as benign cyst, benign solid mass, or malignant solid mass using texture, strain, and morphological features computed from the segmented lesions. Sixty-two breast lesions in US elastography and US B-scan images that are biopsy proved are examined. A classification accuracy using a combination of US elastography and B-scan images is 87.09%, sensitivity 89.29%, specificity 85.29%, positive predictive value 83.33%, and the negative predictive value is 90.63%. With statistically significant features, the classification accuracy using a combination of US elastography and B-scan images is reported to be 82.25% with sensitivity 92.86%, specificity 73.53%, positive predictive value 74.29%, and negative predictive value 92.59%. The classification results indicate that US elastography in combination with US B-mode improves both sensitivity and specificity. © Springer India 2015. Source


Tuz K.,Albany Medical College | Bachmann-Gagescu R.,University of Zurich | O'Day D.R.,University of Washington | Hua K.,Albany Medical College | And 25 more authors.
American Journal of Human Genetics | Year: 2014

Joubert syndrome (JBTS) is a recessive ciliopathy in which a subset of affected individuals also have the skeletal dysplasia Jeune asphyxiating thoracic dystrophy (JATD). Here, we have identified biallelic truncating CSPP1 (centrosome and spindle pole associated protein 1) mutations in 19 JBTS-affected individuals, four of whom also have features of JATD. CSPP1 mutations explain ∼5% of JBTS in our cohort, and despite truncating mutations in all affected individuals, the range of phenotypic severity is broad. Morpholino knockdown of cspp1 in zebrafish caused phenotypes reported in other zebrafish models of JBTS (curved body shape, pronephric cysts, and cerebellar abnormalities) and reduced ciliary localization of Arl13b, further supporting loss of CSPP1 function as a cause of JBTS. Fibroblasts from affected individuals with CSPP1 mutations showed reduced numbers of primary cilia and/or short primary cilia, as well as reduced axonemal localization of ciliary proteins ARL13B and adenylyl cyclase III. In summary, CSPP1 mutations are a major cause of the Joubert-Jeune phenotype in humans; however, the mechanism by which these mutations lead to both JBTS and JATD remains unknown. © 2014 The American Society of Human Genetics. Source

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