The fatigue pre-cracking 304 stainless steel （SS） specimens with lengths of 1.002 mm （L-crack） and 0.575 mm （S-crack） were prepared. Their corrosion behavior was studied by electrochemical noise （EN） in 4 mol/...The fatigue pre-cracking 304 stainless steel （SS） specimens with lengths of 1.002 mm （L-crack） and 0.575 mm （S-crack） were prepared. Their corrosion behavior was studied by electrochemical noise （EN） in 4 mol/L NaC1 ＋ 0.01 mol/L Na2S203 solution under slow-strain-rate-testing （SSRT） conditions. Moreover, the characteristics of L-crack＇s surface morphology and potential distribution with scanning Kelvin probe （SKP） before and after SSRT were also discussed. Compared with S-crack, L-crack is propagated and the features of crack propagation can be obtained. After propagation, the noise amplitudes increase with increasing stress and accelerating corrosion, the white noises at low and high frequencies （WE and WH） of the later stage are one order of magnitude larger than that at early stage in the current power spectral densities （PSDs）. The potential PSDs also increase, but WH disappears. In addition, the crack propagation can be demonstrated according to variation of probability distribution, surface morphology and potential distribution.展开更多
Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 m...Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 male, 7 female, average age 59.4±13.2 years) with pathologically diagnosed pancreatic cancer were enrolled. All patients received an abdominal scan using a dual source CT scanner 7 to 31 days before biopsy or surgery. After injection of iodine contrast agent, arterial and pancreatic parenchyma phase were scanned consequently, using a dual-energy scan mode (100 kVp/230 mAs and Sn 140 kVp/178 mAs) in the pancreatic parenchyma phase. A series of derived dual-energy datasets were evaluated including non-liner blending (non-linear blending width 0-500 HU; blending center -500 to 500 HU), mono-energetic (40-190 keV), 100 kVp and 140 kVp. On each datasets, mean CT values of the pancreatic parenchyma and tumor, as well as standard deviation CT values of subcutaneous fat and psoas muscle were measured. Regions of interest of cutaneous fat and major psoas muscle of 100 kVp and 140 kVp images were calculated. Best CNR of subcutaneous fat (CNR F ) and CNR of the major psoas muscle (CNR M ) of non-liner blending and mono-energetic datasets were calculated with the optimal mono-energetic keV setting and the optimal blending center/width setting for the best CNR. One Way ANOVA test was used for comparison of best CNR between different dual-energy derived datasets. Results The best CNR F (4.48±1.29) was obtained from the non-liner blending datasets at blending center -16.6±103.9 HU and blending width 12.3±10.6 HU. The best CNR F (3.28±0.97) was obtained from the mono-energetic datasets at 73.3±4.3 keV. CNR F in the 100 kVp and 140 kVp were 3.02±0.91 and 1.56±0.56 respectively. Using fat as the noise background, all of these images series showed significant differences (P<0.01) except best CNR F of mono-energetic image sets vs. CNR F of 100 kVp image (P=0.460). Similar results were found using muscle as the noise background (mono-energetic image vs. 100 kVp image: P=0.246; mono-energetic image vs. non-liner blending image: P=0.044; others: P<0.01). Conclusion Compared with mono-energetic datasets and low kVp datasets, non-linear blending image at automatically chosen blending width/window provides better tumor to the pancreas CNR, which might be beneficial for better detection of pancreatic tumors.展开更多
基金Project(2006CB605004) supported by the National Basic Research Program of China
文摘The fatigue pre-cracking 304 stainless steel （SS） specimens with lengths of 1.002 mm （L-crack） and 0.575 mm （S-crack） were prepared. Their corrosion behavior was studied by electrochemical noise （EN） in 4 mol/L NaC1 ＋ 0.01 mol/L Na2S203 solution under slow-strain-rate-testing （SSRT） conditions. Moreover, the characteristics of L-crack＇s surface morphology and potential distribution with scanning Kelvin probe （SKP） before and after SSRT were also discussed. Compared with S-crack, L-crack is propagated and the features of crack propagation can be obtained. After propagation, the noise amplitudes increase with increasing stress and accelerating corrosion, the white noises at low and high frequencies （WE and WH） of the later stage are one order of magnitude larger than that at early stage in the current power spectral densities （PSDs）. The potential PSDs also increase, but WH disappears. In addition, the crack propagation can be demonstrated according to variation of probability distribution, surface morphology and potential distribution.
文摘Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 male, 7 female, average age 59.4±13.2 years) with pathologically diagnosed pancreatic cancer were enrolled. All patients received an abdominal scan using a dual source CT scanner 7 to 31 days before biopsy or surgery. After injection of iodine contrast agent, arterial and pancreatic parenchyma phase were scanned consequently, using a dual-energy scan mode (100 kVp/230 mAs and Sn 140 kVp/178 mAs) in the pancreatic parenchyma phase. A series of derived dual-energy datasets were evaluated including non-liner blending (non-linear blending width 0-500 HU; blending center -500 to 500 HU), mono-energetic (40-190 keV), 100 kVp and 140 kVp. On each datasets, mean CT values of the pancreatic parenchyma and tumor, as well as standard deviation CT values of subcutaneous fat and psoas muscle were measured. Regions of interest of cutaneous fat and major psoas muscle of 100 kVp and 140 kVp images were calculated. Best CNR of subcutaneous fat (CNR F ) and CNR of the major psoas muscle (CNR M ) of non-liner blending and mono-energetic datasets were calculated with the optimal mono-energetic keV setting and the optimal blending center/width setting for the best CNR. One Way ANOVA test was used for comparison of best CNR between different dual-energy derived datasets. Results The best CNR F (4.48±1.29) was obtained from the non-liner blending datasets at blending center -16.6±103.9 HU and blending width 12.3±10.6 HU. The best CNR F (3.28±0.97) was obtained from the mono-energetic datasets at 73.3±4.3 keV. CNR F in the 100 kVp and 140 kVp were 3.02±0.91 and 1.56±0.56 respectively. Using fat as the noise background, all of these images series showed significant differences (P<0.01) except best CNR F of mono-energetic image sets vs. CNR F of 100 kVp image (P=0.460). Similar results were found using muscle as the noise background (mono-energetic image vs. 100 kVp image: P=0.246; mono-energetic image vs. non-liner blending image: P=0.044; others: P<0.01). Conclusion Compared with mono-energetic datasets and low kVp datasets, non-linear blending image at automatically chosen blending width/window provides better tumor to the pancreas CNR, which might be beneficial for better detection of pancreatic tumors.
