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10.2174/1573405612666160519124752 http://scihub22266oqcxt.onion/10.2174/1573405612666160519124752 C5403962!5403962!28491014     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28491014&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\28491014.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Curr+Med+Imaging+Rev 2017 ; 13 (1): 89-98 Nephropedia Template TP {{tp|p=28491014|t=2017. Decision Support System for Lymphoma Classification |pdf=|usr=}}{{28491014}} gab.com Text Decision Support System for Lymphoma Classification JO: Curr Med Imaging Rev http://www.kidney.de/pget.php?&tw=1&pmid=28491014 #FOAvip The diffuse lymphoma is a malignant tumor of lymphoid tissues. It is associated with abnormal, unlimited and uncontrolled proliferation of lymphoid cells. Until now, expert pathologists have identified diffuse lymphoma cells disease manually. This paper introduces automatic system with a friendly user interface to differentiate between the categories of the diffuse lymphoma cells. This research is based on the morphological features such as size, perimeter and circularity. The cell size is a critical element in the classification of diffuse lymphoma according to international formulation standards. Therefore, the applied procedures identify lymphoid cell population in digital microscopic images.The cells are classified using their morphological data according to the characteristics of each cell such as: circularity, perimeter, area, and color density. The number of cells is taken into consideration in the developed approach. Image processing techniques are applied to digital microscopic images to measure morphological parameters and to overcome image problems such as overlapping and cell distortion that affect the sensitivity of the measured data. The developed procedures help the pathologists to come to a decision regarding the classification of diffuse lymphoma. Moreover, it can be used to train medical students and young pathologists. Twit Text FOAVip Decision Support System for Lymphoma Classification ????Curr Med Imaging Rev http://www.kidney.de/pget.php?&tw=1&pmid=28491014 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28491014 #FOAvip English Wikipedia <ref>{{Cite pmid|28491014}}</ref> Decision Support System for Lymphoma Classification #MMPMID28491014 Negm AES; Kandil AH; Hassan OAEF Curr Med Imaging Rev 2017[Feb]; 13 (1): 89-98 PMID28491014show ga The diffuse lymphoma is a malignant tumor of lymphoid tissues. It is associated with abnormal, unlimited and uncontrolled proliferation of lymphoid cells. Until now, expert pathologists have identified diffuse lymphoma cells disease manually. This paper introduces automatic system with a friendly user interface to differentiate between the categories of the diffuse lymphoma cells. This research is based on the morphological features such as size, perimeter and circularity. The cell size is a critical element in the classification of diffuse lymphoma according to international formulation standards. Therefore, the applied procedures identify lymphoid cell population in digital microscopic images.The cells are classified using their morphological data according to the characteristics of each cell such as: circularity, perimeter, area, and color density. The number of cells is taken into consideration in the developed approach. Image processing techniques are applied to digital microscopic images to measure morphological parameters and to overcome image problems such as overlapping and cell distortion that affect the sensitivity of the measured data. The developed procedures help the pathologists to come to a decision regarding the classification of diffuse lymphoma. Moreover, it can be used to train medical students and young pathologists. äDecision Support System for Lymphoma Classification (epmc).pdf DeepDyve Pubget Overpricing