AIM： To find out potential serum hepatocellular carcinoma （HCC）-associated proteins with low molecular weight and low abundance 13y SELDI-based serum protein spectra analysis, that will have much application in the...AIM： To find out potential serum hepatocellular carcinoma （HCC）-associated proteins with low molecular weight and low abundance 13y SELDI-based serum protein spectra analysis, that will have much application in the diagnosis or differentiated diagnosis of HCC, as well as giving a better understanding of the mechanism of hepato-card nogenesis.METHODS： Total serum samples were collected with informed consent from 81 HCC patients with HBV（＋）/ cirrhosis（＋）, 36 cirrhosis patients and 43 chronic hepatitis B patients. Serum protein fingerprint profiles were first generated by selected WCX2 protein chip capture integrating with SELDI-TOF-MS, then normalized and aligned by Ciphergen SELDI Software 3.1.1 with Biomarker Wizard..Comparative analysis of the intensity of corresponding protein fingerprint peaks in normalized protein spectra, some protein peaks with significant difference between H.CC and cirrhosis or chronic hepatitis B were found.RESULTS： One hundred and twenty-eight serum protein peaks betweeri.2000 and 30000Da were identified under the condition of signal-to-noise 〉 5 and minimum threshold for cluster 〉 20%. Eighty-seven of these proteins were showed significant differences in intensity between HCC and cirrhosis （P 〈 0.05）. Of the above differential proteins, 45 proteins had changes greater than two-fold, including 15 upregulated proteins and 30 downregulated proteins i.n HCC serum. Between HCC and chronic hepatitis B, 9 of 52 differential proteins （P 〈 0.05） had intensities of more than two-fold, including 2 upregulated proteins and 7 downregulated proteins in HCC serum. Between cirrhosis and chronic hepatitis B, 28 of 79 significant differential proteins （P 〈 0.05） changes greater than two-fold in intensity, including 17 upregulated proteins and 11 downregulated proteins in cirrhosis serum. For the analysis of these leading differential proteins in subtraction difference mode among three diseases, the five common downregulated proteins in HCC serum （M/Z 2870, 3941, 2688, 3165, 5483） and two common upregulated proteins （M/Z 3588, 2017） in HCC and cirrhosis serum were screened.CONCLUSION： Because the interference of unspecific secreted proteins from hepatitis B and cirrhosis could be eliminated partly in HCC serum under subtraction difference analysis, these seven common differential proteins have the obvious advantage of specificity for evaluating the pathological state of HCC and might become novel candidate biomarkers in the diagnosis of HCC.展开更多
Underwater imaging posts a challenge due to the degradation by the absorption and scattering occurred during light propagation as well as poor lighting conditions in water medium Although image filtering techniques ar...Underwater imaging posts a challenge due to the degradation by the absorption and scattering occurred during light propagation as well as poor lighting conditions in water medium Although image filtering techniques are utilized to improve image quality effectively, problems of the distortion of image details and the bias of color correction still exist in output images due to the complexity of image texture distribution. This paper proposes a new underwater image enhancement method based on image struc- tural decomposition. By introducing a curvature factor into the Mumford_Shah_G decomposition algorithm, image details and struc- ture components are better preserved without the gradient effect. Thus, histogram equalization and Retinex algorithms are applied in the decomposed structure component for global image enhancement and non-uniform brightness correction for gray level and the color images, then the optical absorption spectrum in water medium is incorporate to improve the color correction. Finally, the en- hauced structure and preserved detail component are re.composed to generate the output. Experiments with real underwater images verify the image improvement by the proposed method in image contrast, brightness and color fidelity.展开更多
Automatic reading procedures in colon cells biopsies allow a faster and precise reading of microscopic biopsies. These procedures implement automatic image segmentation in order to classify cell types as cancerous or ...Automatic reading procedures in colon cells biopsies allow a faster and precise reading of microscopic biopsies. These procedures implement automatic image segmentation in order to classify cell types as cancerous or noncancerous. The authors have developed a new approach aiming to detect colon cancer cells derived from the ＂Snake＂ method but using a progressive division of the dimensions of the image to achieve rapid segmentation. The aim of the present paper was to classify different cancerous cell types based on nine morphological parameters and on probabilistic neural network. Three types of cells were used to assess the efficiency of our classifications models, including BH （Benign Hyperplasia）, IN （Intraepithelial Neoplasia） that is a precursor state for cancer, and Ca （Carcinoma） that corresponds to abnormal tissue proliferation （cancer）. Results showed that among the nine parameters used to classify cells, only three morphologic parameters （area, Xor convex and solidity） were found to be effective in distinguishing the three types of cells. In addition, classification of unknown cells was possible using this method.展开更多
文摘AIM： To find out potential serum hepatocellular carcinoma （HCC）-associated proteins with low molecular weight and low abundance 13y SELDI-based serum protein spectra analysis, that will have much application in the diagnosis or differentiated diagnosis of HCC, as well as giving a better understanding of the mechanism of hepato-card nogenesis.METHODS： Total serum samples were collected with informed consent from 81 HCC patients with HBV（＋）/ cirrhosis（＋）, 36 cirrhosis patients and 43 chronic hepatitis B patients. Serum protein fingerprint profiles were first generated by selected WCX2 protein chip capture integrating with SELDI-TOF-MS, then normalized and aligned by Ciphergen SELDI Software 3.1.1 with Biomarker Wizard..Comparative analysis of the intensity of corresponding protein fingerprint peaks in normalized protein spectra, some protein peaks with significant difference between H.CC and cirrhosis or chronic hepatitis B were found.RESULTS： One hundred and twenty-eight serum protein peaks betweeri.2000 and 30000Da were identified under the condition of signal-to-noise 〉 5 and minimum threshold for cluster 〉 20%. Eighty-seven of these proteins were showed significant differences in intensity between HCC and cirrhosis （P 〈 0.05）. Of the above differential proteins, 45 proteins had changes greater than two-fold, including 15 upregulated proteins and 30 downregulated proteins i.n HCC serum. Between HCC and chronic hepatitis B, 9 of 52 differential proteins （P 〈 0.05） had intensities of more than two-fold, including 2 upregulated proteins and 7 downregulated proteins in HCC serum. Between cirrhosis and chronic hepatitis B, 28 of 79 significant differential proteins （P 〈 0.05） changes greater than two-fold in intensity, including 17 upregulated proteins and 11 downregulated proteins in cirrhosis serum. For the analysis of these leading differential proteins in subtraction difference mode among three diseases, the five common downregulated proteins in HCC serum （M/Z 2870, 3941, 2688, 3165, 5483） and two common upregulated proteins （M/Z 3588, 2017） in HCC and cirrhosis serum were screened.CONCLUSION： Because the interference of unspecific secreted proteins from hepatitis B and cirrhosis could be eliminated partly in HCC serum under subtraction difference analysis, these seven common differential proteins have the obvious advantage of specificity for evaluating the pathological state of HCC and might become novel candidate biomarkers in the diagnosis of HCC.
基金supported by the National Natural Science Foundation of China (Grant Nos.60772058 and 61271406)
文摘Underwater imaging posts a challenge due to the degradation by the absorption and scattering occurred during light propagation as well as poor lighting conditions in water medium Although image filtering techniques are utilized to improve image quality effectively, problems of the distortion of image details and the bias of color correction still exist in output images due to the complexity of image texture distribution. This paper proposes a new underwater image enhancement method based on image struc- tural decomposition. By introducing a curvature factor into the Mumford_Shah_G decomposition algorithm, image details and struc- ture components are better preserved without the gradient effect. Thus, histogram equalization and Retinex algorithms are applied in the decomposed structure component for global image enhancement and non-uniform brightness correction for gray level and the color images, then the optical absorption spectrum in water medium is incorporate to improve the color correction. Finally, the en- hauced structure and preserved detail component are re.composed to generate the output. Experiments with real underwater images verify the image improvement by the proposed method in image contrast, brightness and color fidelity.
文摘Automatic reading procedures in colon cells biopsies allow a faster and precise reading of microscopic biopsies. These procedures implement automatic image segmentation in order to classify cell types as cancerous or noncancerous. The authors have developed a new approach aiming to detect colon cancer cells derived from the ＂Snake＂ method but using a progressive division of the dimensions of the image to achieve rapid segmentation. The aim of the present paper was to classify different cancerous cell types based on nine morphological parameters and on probabilistic neural network. Three types of cells were used to assess the efficiency of our classifications models, including BH （Benign Hyperplasia）, IN （Intraepithelial Neoplasia） that is a precursor state for cancer, and Ca （Carcinoma） that corresponds to abnormal tissue proliferation （cancer）. Results showed that among the nine parameters used to classify cells, only three morphologic parameters （area, Xor convex and solidity） were found to be effective in distinguishing the three types of cells. In addition, classification of unknown cells was possible using this method.
