AIM: To explore the quantitative analysis of diffusionweighted magnetic resonance imaging (DWMRI) in differential diagnosis of focal hepatic lesions.METHODS: DWMRI was performed in 149 hepatic lesions, including hepat...AIM: To explore the quantitative analysis of diffusionweighted magnetic resonance imaging (DWMRI) in differential diagnosis of focal hepatic lesions.METHODS: DWMRI was performed in 149 hepatic lesions, including hepatocellular carcinoma (34 cases),hepatic metastases (37 cases), cavernous hemangioma (42 cases), hepatic cyst (36 cases). Apparent diffusion coefficient (ADC) values were evaluated using four different b values in different sequences. The ratio of ADC values of lesion/liver in hepatocellular carcinoma and hepatic metastases was also calculated.RESULTS: The mean ADC values of hepatic lesions were as follows: hepatocellular carcinoma (0.95 ± 0.11) × 10-3 mm2/s, hepatic metastasis (1.13 ± 0.21)× 10-3 mm2/s, cavernous hemangioma (1.86±0.36)×10-3 mm2/s,hepatic cyst(3.14±0.31)×10-3 mm2/s. The ratio of ADC values in lesion/liver in hepatocellular carcinoma was 0.91 ±0.11, being significantly different from that in hepatic metastasis (1.21 ± 0.18, P＜ 0.05).CONCLUSION: ADC values and quantitative analysis of focal hepatic lesions are of significant values in differential diagnosis of focal hepatic lesions.展开更多
Objective To assess the reproducibility of whole-body diffusion weighted imaging(WB-DWI) technique in healthy volunteers under normal breathing with background body signal suppression.Methods WB-DWI was performed on 3...Objective To assess the reproducibility of whole-body diffusion weighted imaging(WB-DWI) technique in healthy volunteers under normal breathing with background body signal suppression.Methods WB-DWI was performed on 32 healthy volunteers twice within two-week period using short TI inversion-recovery diffusion-weighted echo-planar imaging sequence and built-in body coil.The volunteers were scanned across six stations continuously covering the entire body from the head to the feet under normal breathing.The bone apparent diffusion coefficient(ADC) and exponential ADC(eADC) of regions of interest(ROIs) were measured.We analyzed correlation of the results using paired-t-test to assess the reproducibility of the WB-DWI technique.Results We were successful in collecting and analyzing data of 64 WB-DWI images.There was no significant difference in bone ADC and eADC of 824 ROIs between the paired observers and paired scans(P>0.05).Most of the images from all stations were of diagnostic quality.Conclusion The measurements of bone ADC and eADC have good reproducibility.WB-DWI technique under normal breathing with background body signal suppression is adequate.展开更多
Computer-aided diagnosis(CAD) systems have been proposed to assist radiologists in making diagnostic decisions by providing helpful information. As one of the most important sequences in prostate magnetic resonance im...Computer-aided diagnosis(CAD) systems have been proposed to assist radiologists in making diagnostic decisions by providing helpful information. As one of the most important sequences in prostate magnetic resonance imaging(MRI), image features from T2-weighted images(T2WI) were extracted and evaluated for the diagnostic performances by using CAD. We extracted 12 quantitative image features from prostate T2-weighted MR images. The importance of each feature in cancer identification was compared in the peripheral zone(PZ) and central gland(CG), respectively. The performance of the computer-aided diagnosis system supported by an artificial neural network was tested. With computer-aided analysis of T2-weighted images, many characteristic features with different diagnostic capabilities can be extracted. We discovered most of the features(10/12) had significant difference(P<0.01) between PCa and non-PCa in the PZ, while only five features(sum average, minimum value, standard deviation, 10 th percentile, and entropy) had significant difference in CG. CAD prediction by features from T2 w images can reach high accuracy and specificity while maintaining acceptable sensitivity. The outcome is convictive and helpful in medical diagnosis.展开更多
Diffusion-weighted imaging(DWI) is considered to be one of the dominant modalities used in prostate cancer(PCa) detection and the assessment of lesion aggressiveness,especially for peripheral zone(PZ) PCa.Computer-aid...Diffusion-weighted imaging(DWI) is considered to be one of the dominant modalities used in prostate cancer(PCa) detection and the assessment of lesion aggressiveness,especially for peripheral zone(PZ) PCa.Computer-aided diagnosis(CAD),which is capable of automatically extracting and evaluating image features,can integrate multiple parameters and improve the detection of PCa.In this study,13 quantitative image features were extracted from DWI by CAD,and diagnostic efficacy was analyzed in both the PZ and transition zone(TZ).The results demonstrated that there was a significant difference(P<0.05) between PCa and non-PCa for nine of the 13 features in the PZ and five of the 13 features in the TZ.Besides,the prediction outcome of CAD had a strong correlation with the DWI scores that were graded by experienced radiologists according to the Prostate Imaging-Reporting and Data System Version 2(PI-RADS v2).展开更多
文摘多Agent系统(Multi-Agent System,MAS)是人工智能领域的一个非常活跃的研究方向。在多Agent系统中,由于Agent之间信念的差异,会不可避免地造成行动冲突。Sakama等提出的严格协调方法只适用于各Agent之间有共同信念的情境,当不存在共同信念时,此协调方法无解。针对该问题,文中提出了一种基于可能回答集程序(Possibilistic Answer Set Programming,PASP)的信念协调方法。首先,针对各Agent的不同信念集,基于加权定量的方法计算PASP的回答集相对Agent信念的满足度,以此来弱化某些信念,并且引入缺省决策理论推理得到Agent信念协调的一致解。然后,根据一致解建立一致的协调程序,将其作为Agent共同认同的背景知识库。最后,以dlv求解器为基础实现了多Agent信念协调算法,使Agent之间可以自主完成信念协调。文中以旅游推荐系统为例,说明该算法能够打破严格协调方法的局限,有效解决各Agent之间无共同信念时的协调问题。
基金Supported by the Natural Science Foundation of Guangdong Province, China, No. 32830 and 101595
文摘AIM: To explore the quantitative analysis of diffusionweighted magnetic resonance imaging (DWMRI) in differential diagnosis of focal hepatic lesions.METHODS: DWMRI was performed in 149 hepatic lesions, including hepatocellular carcinoma (34 cases),hepatic metastases (37 cases), cavernous hemangioma (42 cases), hepatic cyst (36 cases). Apparent diffusion coefficient (ADC) values were evaluated using four different b values in different sequences. The ratio of ADC values of lesion/liver in hepatocellular carcinoma and hepatic metastases was also calculated.RESULTS: The mean ADC values of hepatic lesions were as follows: hepatocellular carcinoma (0.95 ± 0.11) × 10-3 mm2/s, hepatic metastasis (1.13 ± 0.21)× 10-3 mm2/s, cavernous hemangioma (1.86±0.36)×10-3 mm2/s,hepatic cyst(3.14±0.31)×10-3 mm2/s. The ratio of ADC values in lesion/liver in hepatocellular carcinoma was 0.91 ±0.11, being significantly different from that in hepatic metastasis (1.21 ± 0.18, P＜ 0.05).CONCLUSION: ADC values and quantitative analysis of focal hepatic lesions are of significant values in differential diagnosis of focal hepatic lesions.
文摘Objective To assess the reproducibility of whole-body diffusion weighted imaging(WB-DWI) technique in healthy volunteers under normal breathing with background body signal suppression.Methods WB-DWI was performed on 32 healthy volunteers twice within two-week period using short TI inversion-recovery diffusion-weighted echo-planar imaging sequence and built-in body coil.The volunteers were scanned across six stations continuously covering the entire body from the head to the feet under normal breathing.The bone apparent diffusion coefficient(ADC) and exponential ADC(eADC) of regions of interest(ROIs) were measured.We analyzed correlation of the results using paired-t-test to assess the reproducibility of the WB-DWI technique.Results We were successful in collecting and analyzing data of 64 WB-DWI images.There was no significant difference in bone ADC and eADC of 824 ROIs between the paired observers and paired scans(P>0.05).Most of the images from all stations were of diagnostic quality.Conclusion The measurements of bone ADC and eADC have good reproducibility.WB-DWI technique under normal breathing with background body signal suppression is adequate.
基金Supported by the Natural Science Foundation of Fujian Province(No.2021J05188)the Scientific Research Project of the Education Department of Fujian Province(No.JAT200331)+1 种基金President’s Fund of Minnan Normal University(No.KJ2020020)Fujian Key Laboratory of Granular Computing and Applications,Institute of Meteorological Big Data-Digital Fujian and Fujian Key Laboratory of Data Science and Statistics(Minnan Normal University).
文摘Computer-aided diagnosis(CAD) systems have been proposed to assist radiologists in making diagnostic decisions by providing helpful information. As one of the most important sequences in prostate magnetic resonance imaging(MRI), image features from T2-weighted images(T2WI) were extracted and evaluated for the diagnostic performances by using CAD. We extracted 12 quantitative image features from prostate T2-weighted MR images. The importance of each feature in cancer identification was compared in the peripheral zone(PZ) and central gland(CG), respectively. The performance of the computer-aided diagnosis system supported by an artificial neural network was tested. With computer-aided analysis of T2-weighted images, many characteristic features with different diagnostic capabilities can be extracted. We discovered most of the features(10/12) had significant difference(P<0.01) between PCa and non-PCa in the PZ, while only five features(sum average, minimum value, standard deviation, 10 th percentile, and entropy) had significant difference in CG. CAD prediction by features from T2 w images can reach high accuracy and specificity while maintaining acceptable sensitivity. The outcome is convictive and helpful in medical diagnosis.
文摘Diffusion-weighted imaging(DWI) is considered to be one of the dominant modalities used in prostate cancer(PCa) detection and the assessment of lesion aggressiveness,especially for peripheral zone(PZ) PCa.Computer-aided diagnosis(CAD),which is capable of automatically extracting and evaluating image features,can integrate multiple parameters and improve the detection of PCa.In this study,13 quantitative image features were extracted from DWI by CAD,and diagnostic efficacy was analyzed in both the PZ and transition zone(TZ).The results demonstrated that there was a significant difference(P<0.05) between PCa and non-PCa for nine of the 13 features in the PZ and five of the 13 features in the TZ.Besides,the prediction outcome of CAD had a strong correlation with the DWI scores that were graded by experienced radiologists according to the Prostate Imaging-Reporting and Data System Version 2(PI-RADS v2).
