脑梗塞的磁共振成像与临床

本文讨论了80例脑梗塞磁共振成像与临床表现,其中20例有CT检查。多数病例磁共振成像显示为多发性脑梗塞(95%)。梗塞灶在T_1加权是低信号改变;T_2加权呈高信号改变,急性和慢性期特点一致。资料结果表明:磁共振成像定位准确(98.75%)。病灶检出T_2比T_1敏感,磁共振成像检出病灶多于CT。在诊断脑梗塞方面,磁共振成像优于CT。     

整数微分进化策略及其在微波成像中的应用

提出了微分进化策略的整数编码方法.按照给定的精度使优化问题的常规实数编码的解空间离散化,并对离散化的结果进行整数编码,建立对应的整数空间.在整数空间中求解,在实数空间中计算解的适应度.对有限精度以及计算存在离散化过程的工程优化问题,用整数编码可有效提高搜索速度,并自动滤除不稳定解.对于离散、高维、多值类型的微波成像示例,与实数编码比较,用微分进化策略的整数编码优化算法搜索速度更高,成像结果更优.     

析晶过程中盐渍土的微观结构变化

为了揭示易溶盐析晶过程中对盐渍土强度的影响机理,用环境扫描电子显微镜及X射线能谱（EDX）,对盐渍土的微观结构进行了分析,探讨了易溶盐析晶对土强度的影响;通过对自然脱水干燥前后盐渍土的强度试验,探讨了微观结构变化对土强度的影响.研究结果表明：析晶前后盐渍土的微观结构特征明显不同——析晶前为盐-土混容态包裹土团粒结构;析晶后为晶体土颗粒共混结构,从而使土体强度显著提高.     

张口上仰位三相骨显像对颞颌关节紊乱综合征的诊断

研究放射性核素三相骨显像对颞颌关节紊乱综合征的早期诊断价值。方法　采用常规前位及张口上仰位对 2 2例颞颌关节综合征患者进行了三相骨显像。结果　常规前位及张口上仰位三相骨显像对颞颌关节紊乱综合征的阳性检出率分别为 70 .83%、87.50 %。张口上仰位三相骨显像患健侧颞颌关节放射性比值在血流相对峰值比为 1 .53± 0 .2 9,在延迟相时为 1 .57±0 .2 3,与常规前位采集均有显著性差异 ( P <0 .0 1 )。结论　张口上仰位三相骨显像能早期诊断颞颌关节紊乱综合征     

肝移植术后并发症的影像学诊断

目的系统分析肝移植术后正常及常见并发症的影像学表现。方法使用Philips Secura螺旋CT扫描仪对50例肝移植术后患者进行检查,CT扫描范围自膈顶至腰3椎体下缘水平,对比剂1.3mL/kg体质量,注药流率2.5mL/s,延迟时间30、60、120s。对拔除T管后出现胆管并发症患者使用Philips Gyroscan NT1.5T磁共振扫描仪检查。使用GE Advance Lp/Lc数字血管造影机,经股动脉穿刺进行肝动脉造影。结果27例肝移植术后患者出现移植肝下积液及右侧胸腔积液,门静脉伴行影像4例,肝动脉吻合口狭窄2例,肝动脉血栓1例,门静脉吻合口狭窄2例,胆管吻合口部位狭窄1例,非吻合口狭窄3例,胆瘘4例,肿瘤复发4例。结论CT、磁共振胆道水成像(MRCP)和数字减影(DSA)可以清晰显示肝移植术后血管、胆管并发症及其他少见并发症。     

大鼠移植性肝癌MRI信号特征与定量分析

通过对Ｗａｌｋｅｒ２５６移植性肝癌的动物模型的ＭＲＩ图像信号以及Ｔ１值、Ｔ２值的测定分析，提出了在０．３５Ｔ磁场强度下大鼠移植性肝癌ＭＲＩ信号定量分析的模式和意义。提出：（１）大鼠移植瘤的Ｔ１值与正常肝组织Ｔ１值有较大重叠，诊断意义不大；（２）移植瘤Ｔ２值与正常厅组织Ｔ２值无重叠有诊断意义；（３）移植瘤Ｔ２ＷＩ－ＳＩＲ值亦具有诊断意义。建议各种不同磁场强度的机器可建立自己的定量分析标准。     

Response of benthic infauna and epifauna to ocean disposal of red clay dredged material in the New York Bight: A study using sediment-profile imaging, surface imaging and traditional methods

In 1997, approximately 1 million cubic yards of consolidated red clay was dredged from Newark Bay in New Jersey and deposited on the seafloor at an open-water dredged material disposal site located on the inner continental shelf of the New York Bight. To address concerns about the ability of benthic organisms to colonize the seafloor deposits of this compact, organic-poor red clay, monitoring surveys were conducted in 1998 (1 year after disposal) and 2002 (5 years after disposal). The surveys used a combination of sediment imaging and traditional grab sampling methods to characterize physical and biological conditions over the surface of the red clay deposits in comparison to nearby reference areas consisting of either naturally-occurring, sandy surface sediments or deposits of unconsolidated, muddy dredged material. Sediment-surface and sediment-profile images (SPI) collected in summer 2002 indicated that the surface of the red clay deposits had become much smoother and more heterogeneous in texture compared to images collected in 1998. The images also indicated that these deposits had become colonized to a much greater degree by relatively abundant and diverse infaunal and epifaunal communities compared to 1998. Taxonomic analysis of benthic grab samples confirmed the imaging results and indicated relatively high infaunal organism abundance and diversity over the red clay deposits in 2002 compared to the reference areas. However, the structure of the benthic community inhabiting the red clay was fundamentally different from the communities in the reference areas, due to the differences in sediment texture and composition. The combination of imaging and traditional taxonomic approaches used in this study provided much greater insight on the red clay colonization process than either approach by itself.     

Underwater acoustic imaging: image due to a specular reflector in the geometrical-acoustics limit

In underwater acoustic imaging, which is used to produce high-quality images in turbid waters, a specular reflector can produce a “pseudoimage” of the receiving array at the reflecting surface. Based on the “geometrical approximation” (which is similar to geometrical acoustics), formulae are derived for the size and shape of the pseudoimage for both flat and curved reflectors. For curved reflectors, described by two principal radii of curvature, the formulae also assume the “large-range approximation.” The formulae allow radii of curvature to be determined from an image. Also discussed briefly are some possible extensions and the role of nongeometrical effects.     

Propagation characteristics of elastic wave in layered medium and applications of impact imaging method

It is an important subject to probe the structure in the medium by various kinds of detection methods in the geotechnical engineering. Based on the propagation theory of elastic wave in half-space layered medium, the propagation characteristics of elastic wave in layered medium with different elastic parameters are discussed using dynamic analysis of finite element method. It is known that the S-wave velocity, density and thickness of layer are related to the properties of the elastic wave including waveform characteristics, spectral characteristics and time-frequency characteristics. We pay special attention to the structure with low velocity interlayer. The impact imaging method is applied to the grouting construction of the immersed tube tunnel. Data acquisition and analytical method are introduced in detail. The grouting effects can be qualitatively evaluated by comparing the characteristics of elastic wave before grouting with those after grouting. Finally, a quantitative evaluation is obtained according to the relationship between energy response of elastic wave and impedance ratio.     

COVID-19 Interpretable Diagnosis Algorithm Based on a Small Number of Chest X-Ray Samples

The COVID-19 medical diagnosis method based on individual's chest X-ray (CXR) is achieved dif-ficultly in the initial research,owing to difficulties in identifying CXR data of COVID-19 individuals.At the beginning of the study,infected individuals' CXRs were scarce.The combination of artificial intelligence (AI)and medical diagnosis has been advanced and popular.To solve the difficulties,the interpretability analysis of AI model was used to explore the pathological characteristics of CXR samples infected with COVID-19 and assist in medical diagnosis.The dataset was expanded by data augmentation to avoid overfitting.Transfer learning was used to test different pre-trained models and the unique output layers were designed to complete the model training with few samples.In this study,the output results of four pre-trained models in three different output layers were compared,and the results after data augmentation were compared with the results of the original dataset.The control variable method was used to conduct independent tests of 24 groups.Finally,99.23％ accuracy and 98％recall rate were obtained,and the visual results of CXR interpretability analysis were displayed.The network of COVID-19 interpretable diagnosis algorithm has the characteristics of high generalization and lightweight.It can be quickly applied to other urgent tasks with insufficient experimental data.At the same time,interpretability analysis brings new possibilities for medical diagnosis.