Background Deep convolutional neural networks have garnered considerable attention in numerous machine learning applications,particularly in visual recognition tasks such as image and video analyses.There is a growing...Background Deep convolutional neural networks have garnered considerable attention in numerous machine learning applications,particularly in visual recognition tasks such as image and video analyses.There is a growing interest in applying this technology to diverse applications in medical image analysis.Automated three dimensional Breast Ultrasound is a vital tool for detecting breast cancer,and computer-assisted diagnosis software,developed based on deep learning,can effectively assist radiologists in diagnosis.However,the network model is prone to overfitting during training,owing to challenges such as insufficient training data.This study attempts to solve the problem caused by small datasets and improve model detection performance.Methods We propose a breast cancer detection framework based on deep learning(a transfer learning method based on cross-organ cancer detection)and a contrastive learning method based on breast imaging reporting and data systems(BI-RADS).Results When using cross organ transfer learning and BIRADS based contrastive learning,the average sensitivity of the model increased by a maximum of 16.05%.Conclusion Our experiments have demonstrated that the parameters and experiences of cross-organ cancer detection can be mutually referenced,and contrastive learning method based on BI-RADS can improve the detection performance of the model.展开更多
Methane gas hydrate related bottom-simulating reflectors(BSRs)are imaged based on the in-line and cross-line multi-channel seismic(MCS)data from the Andaman Forearc Basin.The depth of the BSR depends on pressure and t...Methane gas hydrate related bottom-simulating reflectors(BSRs)are imaged based on the in-line and cross-line multi-channel seismic(MCS)data from the Andaman Forearc Basin.The depth of the BSR depends on pressure and temperature and pore water salinity.With these assumptions,the BSR depth can be used to estimate the geothermal gradient(GTG)based on the availability of in-situ temperature measurements.This calculation is done assuming a 1D conductive model based on available in-situ temperature measurement at site NGHP-01-17 in the study area.However,in the presence of seafloor topography,the conductive temperature field in the subsurface is affected by lateral refraction of heat,which focuses heat in topographic lows and away from topographic highs.The 1D estimate of GTG in the Andaman Forearc Basin has been validated by drilling results from the NGHP-01 expedition.2D analytic modeling to estimate the effects of topography is performed earlier along selected seismic profiles in the study area.The study extended to estimate the effect of topography in 3D using a numerical model.The corrected GTG data allow us to determine GTG values free of topographic effect.The difference between the estimated GTG and values corrected for the 3D topographic effect varies up to~5℃/km.These conclude that the topographic correction is relatively small compared to other uncertainties in the 1D model and that apparent GTG determined with the 1D model captures the major features,although the correction is needed prior to interpreting subtle features of the derived GTG maps.展开更多
Purpose: This review examines the diagnostic value of transvaginal 3D ultrasound image texture analysis for the diagnosis of uterine adhesions. Materials and Methods: The total clinical data of 53 patients with uterin...Purpose: This review examines the diagnostic value of transvaginal 3D ultrasound image texture analysis for the diagnosis of uterine adhesions. Materials and Methods: The total clinical data of 53 patients with uterine adhesions diagnosed by hysteroscopy and the imaging data of transvaginal three-dimensional ultrasound from the Second Affiliated Hospital of Chongqing Medical University from June 2022 to August 2023 were retrospectively analysed. Based on hysteroscopic surgical records, patients were divided into two independent groups: normal endometrium and uterine adhesion sites. The samples were divided into a training set and a test set, and the transvaginal 3D ultrasound was used to outline the region of interest (ROI) and extract texture features for normal endometrium and uterine adhesions based on hysteroscopic surgical recordings, the training set data were feature screened and modelled using lasso regression and cross-validation, and the diagnostic efficacy of the model was assessed by applying the subjects’ operating characteristic (ROC) curves. Results: For each group, 290 texture feature parameters were extracted and three higher values were screened out, and the area under the curve of the constructed ultrasonographic scoring model was 0.658 and 0.720 in the training and test sets, respectively. Conclusion Relative clinical value of transvaginal three-dimensional ultrasound image texture analysis for the diagnosis of uterine adhesions.展开更多
Objective:To study the clinical outcomes of complete mesocolic excision(CME)for right-sided colon cancer using 3D(three-dimensional)laparoscopy compared to 2D(two-dimensional)laparoscopy.Methods:From January 2022 to D...Objective:To study the clinical outcomes of complete mesocolic excision(CME)for right-sided colon cancer using 3D(three-dimensional)laparoscopy compared to 2D(two-dimensional)laparoscopy.Methods:From January 2022 to December 2023,58 patients with right-sided colon cancer treated at the Affiliated Hospital of Hebei Engineering University were randomly divided into a 3D laparoscopy group(observation group)and a 2D laparoscopy group(control group),with 29 patients in each group.Intraoperative blood loss,postoperative time to first flatulence,length of hospital stay,and incidence of complications in both groups were recorded.Results:There was a statistically significant difference in intraoperative blood loss between the two groups(P<0.05).There was no statistically significant difference in the time to first flatulence between the groups(P>0.05).However,there was a statistically significant difference in the length of hospital stay(P<0.05)and the incidence of complications(P<0.05)between the two groups.Conclusion:3D laparoscopy for CME can reduce intraoperative blood loss,shorten hospital stay,and decrease postoperative complications,showing significant clinical advantages over traditional 2D laparoscopy.展开更多
基金Macao Polytechnic University Grant(RP/FCSD-01/2022RP/FCA-05/2022)Science and Technology Development Fund of Macao(0105/2022/A).
文摘Background Deep convolutional neural networks have garnered considerable attention in numerous machine learning applications,particularly in visual recognition tasks such as image and video analyses.There is a growing interest in applying this technology to diverse applications in medical image analysis.Automated three dimensional Breast Ultrasound is a vital tool for detecting breast cancer,and computer-assisted diagnosis software,developed based on deep learning,can effectively assist radiologists in diagnosis.However,the network model is prone to overfitting during training,owing to challenges such as insufficient training data.This study attempts to solve the problem caused by small datasets and improve model detection performance.Methods We propose a breast cancer detection framework based on deep learning(a transfer learning method based on cross-organ cancer detection)and a contrastive learning method based on breast imaging reporting and data systems(BI-RADS).Results When using cross organ transfer learning and BIRADS based contrastive learning,the average sensitivity of the model increased by a maximum of 16.05%.Conclusion Our experiments have demonstrated that the parameters and experiences of cross-organ cancer detection can be mutually referenced,and contrastive learning method based on BI-RADS can improve the detection performance of the model.
文摘Methane gas hydrate related bottom-simulating reflectors(BSRs)are imaged based on the in-line and cross-line multi-channel seismic(MCS)data from the Andaman Forearc Basin.The depth of the BSR depends on pressure and temperature and pore water salinity.With these assumptions,the BSR depth can be used to estimate the geothermal gradient(GTG)based on the availability of in-situ temperature measurements.This calculation is done assuming a 1D conductive model based on available in-situ temperature measurement at site NGHP-01-17 in the study area.However,in the presence of seafloor topography,the conductive temperature field in the subsurface is affected by lateral refraction of heat,which focuses heat in topographic lows and away from topographic highs.The 1D estimate of GTG in the Andaman Forearc Basin has been validated by drilling results from the NGHP-01 expedition.2D analytic modeling to estimate the effects of topography is performed earlier along selected seismic profiles in the study area.The study extended to estimate the effect of topography in 3D using a numerical model.The corrected GTG data allow us to determine GTG values free of topographic effect.The difference between the estimated GTG and values corrected for the 3D topographic effect varies up to~5℃/km.These conclude that the topographic correction is relatively small compared to other uncertainties in the 1D model and that apparent GTG determined with the 1D model captures the major features,although the correction is needed prior to interpreting subtle features of the derived GTG maps.
文摘Purpose: This review examines the diagnostic value of transvaginal 3D ultrasound image texture analysis for the diagnosis of uterine adhesions. Materials and Methods: The total clinical data of 53 patients with uterine adhesions diagnosed by hysteroscopy and the imaging data of transvaginal three-dimensional ultrasound from the Second Affiliated Hospital of Chongqing Medical University from June 2022 to August 2023 were retrospectively analysed. Based on hysteroscopic surgical records, patients were divided into two independent groups: normal endometrium and uterine adhesion sites. The samples were divided into a training set and a test set, and the transvaginal 3D ultrasound was used to outline the region of interest (ROI) and extract texture features for normal endometrium and uterine adhesions based on hysteroscopic surgical recordings, the training set data were feature screened and modelled using lasso regression and cross-validation, and the diagnostic efficacy of the model was assessed by applying the subjects’ operating characteristic (ROC) curves. Results: For each group, 290 texture feature parameters were extracted and three higher values were screened out, and the area under the curve of the constructed ultrasonographic scoring model was 0.658 and 0.720 in the training and test sets, respectively. Conclusion Relative clinical value of transvaginal three-dimensional ultrasound image texture analysis for the diagnosis of uterine adhesions.
文摘Objective:To study the clinical outcomes of complete mesocolic excision(CME)for right-sided colon cancer using 3D(three-dimensional)laparoscopy compared to 2D(two-dimensional)laparoscopy.Methods:From January 2022 to December 2023,58 patients with right-sided colon cancer treated at the Affiliated Hospital of Hebei Engineering University were randomly divided into a 3D laparoscopy group(observation group)and a 2D laparoscopy group(control group),with 29 patients in each group.Intraoperative blood loss,postoperative time to first flatulence,length of hospital stay,and incidence of complications in both groups were recorded.Results:There was a statistically significant difference in intraoperative blood loss between the two groups(P<0.05).There was no statistically significant difference in the time to first flatulence between the groups(P>0.05).However,there was a statistically significant difference in the length of hospital stay(P<0.05)and the incidence of complications(P<0.05)between the two groups.Conclusion:3D laparoscopy for CME can reduce intraoperative blood loss,shorten hospital stay,and decrease postoperative complications,showing significant clinical advantages over traditional 2D laparoscopy.
