This paper deals with the temperature correlation of gray scale of B-mode ultrasound image from heated tissue. In this study, many in-vitro fresh pig livers are heated in a temperature range from 28 ℃ to 45℃, from w...This paper deals with the temperature correlation of gray scale of B-mode ultrasound image from heated tissue. In this study, many in-vitro fresh pig livers are heated in a temperature range from 28 ℃ to 45℃, from which a series of B-mode ultrasonic images of livers were obtained. The gray-value is evaluated from the ultrasound images respectively. A correlation of the mean gray value of the selected regions (12×12 pixels) in B-mode ultrasonic images of liver and its temperature was pointed out. And the experiment results agreed the evaluation well. And it is possible to monitor the tissue temperature changing in hyperthermia using this correlation.展开更多
Objective To study the role of bladder trabeculation found by B-mode ultrasound in evaluating the degree of bladder outlet obstruction ( BOO ) and the bladder function in benign prostatic hyperplasia ( BPH) patients. ...Objective To study the role of bladder trabeculation found by B-mode ultrasound in evaluating the degree of bladder outlet obstruction ( BOO ) and the bladder function in benign prostatic hyperplasia ( BPH) patients. Methods Conducted prospective research to determine differences in clinical data and urodynamic展开更多
Artificial intelligence (AI)-based radiomics has attracted considerable research attention in the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique advantages such as high tempora...Artificial intelligence (AI)-based radiomics has attracted considerable research attention in the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique advantages such as high temporal resolution, low cost, and no radiation exposure. This renders it a preferred imaging modality for several clinical scenarios. This review includes a detailed introduction to imaging modalities, including Brightness-mode ultrasound, color Doppler flow imaging, ultrasound elastography, contrast-enhanced ultrasound, and multi-modal fusion analysis. It provides an overview of the current status and prospects of AI-based radiomics in ultrasound diagnosis, highlighting the application of AI-based radiomics to static ultrasound images, dynamic ultrasound videos, and multi-modal ultrasound fusion analysis.展开更多
Deep neural network(DNN)based computer-aided breast tumor diagnosis(CABTD)method plays a vital role in the early detection and diagnosis of breast tumors.However,a Brightness mode(B-mode)ultrasound image derives train...Deep neural network(DNN)based computer-aided breast tumor diagnosis(CABTD)method plays a vital role in the early detection and diagnosis of breast tumors.However,a Brightness mode(B-mode)ultrasound image derives training feature samples that make closer isolation toward the infection part.Hence,it is expensive due to a metaheuristic search of features occupying the global region of interest(ROI)structures of input images.Thus,it may lead to the high computational complexity of the pre-trained DNN-based CABTD method.This paper proposes a novel ensemble pretrained DNN-based CABTD method using global-and local-ROI-structures of B-mode ultrasound images.It conveys the additional consideration of a local-ROI-structures for further enhan-cing the pretrained DNN-based CABTD method’s breast tumor diagnostic performance without degrading its visual quality.The features are extracted at various depths(18,50,and 101)from the global and local ROI structures and feed to support vector machine for better classification.From the experimental results,it has been observed that the combined local and global ROI structure of small depth residual network ResNet18(0.8 in%)has produced significant improve-ment in pixel ratio as compared to ResNet50(0.5 in%)and ResNet101(0.3 in%),respectively.Subsequently,the pretrained DNN-based CABTD methods have been tested by influencing local and global ROI structures to diagnose two specific breast tumors(Benign and Malignant)and improve the diagnostic accuracy(86%)compared to Dense Net,Alex Net,VGG Net,and Google Net.Moreover,it reduces the computational complexity due to the small depth residual network ResNet18,respectively.展开更多
目的:观察经直肠超声组织弹性成像技术在前列腺癌穿刺诊断中的应用,探讨其在前列腺良恶性结节靶向穿刺中的应用价值。方法:收集2013年2月至2016年6月在我院泌尿外科收治的患者50例,对该50例患者行血清前列腺特异抗原(prostate specific ...目的:观察经直肠超声组织弹性成像技术在前列腺癌穿刺诊断中的应用,探讨其在前列腺良恶性结节靶向穿刺中的应用价值。方法:收集2013年2月至2016年6月在我院泌尿外科收治的患者50例,对该50例患者行血清前列腺特异抗原(prostate specific antigen,PSA)检查,对于PSA升高且临床高度怀疑前列腺癌的患者行前列腺穿刺活检,在行穿刺前,对该50例患者均行常规经直肠超声(TRUS)检查,之后再进行TRE检查,将弹性检查图像显示为蓝色的区域(硬度较高区域)定义为前列腺癌可疑区,随后对患者进行穿刺活检,首先行标准12点活检方案,再对可疑结节进行靶向穿刺2或3针,以超声引导下经直肠前列腺穿刺活检病理结果为金标准,将其与超声检查(包括TRUS及TRE)结果进行对照分析。结果:50例患者中病理证实恶性病变35例,良性病变15例,TRUS诊断良性病变40例,恶性病变10例,其特异度、灵敏度、阴性预测值、阳性预测值、误诊率、准确率分别为:80%、24%、37.5%、80%、20%、46%,结合弹性成像技术后诊断良性病变20例,恶性病变30例,其特异度、灵敏度、阴性预测值、阳性预测值、误诊率、准确率分别为:75%、83%、75.5%、83%、54%、80%。结论:经直肠超声组织弹性成像技术在一定程度上可以引导前列腺癌病灶进行目标活检,提高前列腺癌穿刺诊断阳性率。展开更多
基金The research was supported by National Nature Science Foundation (30470450) Education Committee Foundation( KP0608200201 ) Elitist Foundation( KW5800200351 ) from Beijing City,China.
文摘This paper deals with the temperature correlation of gray scale of B-mode ultrasound image from heated tissue. In this study, many in-vitro fresh pig livers are heated in a temperature range from 28 ℃ to 45℃, from which a series of B-mode ultrasonic images of livers were obtained. The gray-value is evaluated from the ultrasound images respectively. A correlation of the mean gray value of the selected regions (12×12 pixels) in B-mode ultrasonic images of liver and its temperature was pointed out. And the experiment results agreed the evaluation well. And it is possible to monitor the tissue temperature changing in hyperthermia using this correlation.
文摘Objective To study the role of bladder trabeculation found by B-mode ultrasound in evaluating the degree of bladder outlet obstruction ( BOO ) and the bladder function in benign prostatic hyperplasia ( BPH) patients. Methods Conducted prospective research to determine differences in clinical data and urodynamic
基金the National Natural Science Foundation of China,Nos.92159305,92259303,62027901,81930053,and 82272029Beijing Science Fund for Distinguished Young Scholars,No.JQ22013and Excellent Member Project of the Youth Innovation Promotion Association CAS,No.2016124.
文摘Artificial intelligence (AI)-based radiomics has attracted considerable research attention in the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique advantages such as high temporal resolution, low cost, and no radiation exposure. This renders it a preferred imaging modality for several clinical scenarios. This review includes a detailed introduction to imaging modalities, including Brightness-mode ultrasound, color Doppler flow imaging, ultrasound elastography, contrast-enhanced ultrasound, and multi-modal fusion analysis. It provides an overview of the current status and prospects of AI-based radiomics in ultrasound diagnosis, highlighting the application of AI-based radiomics to static ultrasound images, dynamic ultrasound videos, and multi-modal ultrasound fusion analysis.
文摘Deep neural network(DNN)based computer-aided breast tumor diagnosis(CABTD)method plays a vital role in the early detection and diagnosis of breast tumors.However,a Brightness mode(B-mode)ultrasound image derives training feature samples that make closer isolation toward the infection part.Hence,it is expensive due to a metaheuristic search of features occupying the global region of interest(ROI)structures of input images.Thus,it may lead to the high computational complexity of the pre-trained DNN-based CABTD method.This paper proposes a novel ensemble pretrained DNN-based CABTD method using global-and local-ROI-structures of B-mode ultrasound images.It conveys the additional consideration of a local-ROI-structures for further enhan-cing the pretrained DNN-based CABTD method’s breast tumor diagnostic performance without degrading its visual quality.The features are extracted at various depths(18,50,and 101)from the global and local ROI structures and feed to support vector machine for better classification.From the experimental results,it has been observed that the combined local and global ROI structure of small depth residual network ResNet18(0.8 in%)has produced significant improve-ment in pixel ratio as compared to ResNet50(0.5 in%)and ResNet101(0.3 in%),respectively.Subsequently,the pretrained DNN-based CABTD methods have been tested by influencing local and global ROI structures to diagnose two specific breast tumors(Benign and Malignant)and improve the diagnostic accuracy(86%)compared to Dense Net,Alex Net,VGG Net,and Google Net.Moreover,it reduces the computational complexity due to the small depth residual network ResNet18,respectively.
文摘目的:观察经直肠超声组织弹性成像技术在前列腺癌穿刺诊断中的应用,探讨其在前列腺良恶性结节靶向穿刺中的应用价值。方法:收集2013年2月至2016年6月在我院泌尿外科收治的患者50例,对该50例患者行血清前列腺特异抗原(prostate specific antigen,PSA)检查,对于PSA升高且临床高度怀疑前列腺癌的患者行前列腺穿刺活检,在行穿刺前,对该50例患者均行常规经直肠超声(TRUS)检查,之后再进行TRE检查,将弹性检查图像显示为蓝色的区域(硬度较高区域)定义为前列腺癌可疑区,随后对患者进行穿刺活检,首先行标准12点活检方案,再对可疑结节进行靶向穿刺2或3针,以超声引导下经直肠前列腺穿刺活检病理结果为金标准,将其与超声检查(包括TRUS及TRE)结果进行对照分析。结果:50例患者中病理证实恶性病变35例,良性病变15例,TRUS诊断良性病变40例,恶性病变10例,其特异度、灵敏度、阴性预测值、阳性预测值、误诊率、准确率分别为:80%、24%、37.5%、80%、20%、46%,结合弹性成像技术后诊断良性病变20例,恶性病变30例,其特异度、灵敏度、阴性预测值、阳性预测值、误诊率、准确率分别为:75%、83%、75.5%、83%、54%、80%。结论:经直肠超声组织弹性成像技术在一定程度上可以引导前列腺癌病灶进行目标活检,提高前列腺癌穿刺诊断阳性率。
