1概述肺癌是最常见的恶性肿瘤之一,在世界各地,肺癌均居恶性肿瘤死亡构成比的第一位,其发病率和死亡率仍在不断升高。据世界卫生组织（World Health Organization,WHO）下属的国际癌症研究机构（International Agency for Research on C...1概述肺癌是最常见的恶性肿瘤之一,在世界各地,肺癌均居恶性肿瘤死亡构成比的第一位,其发病率和死亡率仍在不断升高。据世界卫生组织（World Health Organization,WHO）下属的国际癌症研究机构（International Agency for Research on Cancer,IARC）出版的GLOBOCAN 2012估计：全世界肺癌新发病例1 8 2.5万（男性124.2万,女性58.3万）.展开更多
Over the past two decades, advances in cross-sectionalimaging such as computed tomography and magneticresonance imaging(MRI) have dramatically changed theconcept of gastrointestinal imaging. MR is playing anincreasing...Over the past two decades, advances in cross-sectionalimaging such as computed tomography and magneticresonance imaging(MRI) have dramatically changed theconcept of gastrointestinal imaging. MR is playing anincreasing role in the evaluation of gastrointestinal disorders. MRI combines the advantages of excellent soft-tissue contrast, noninvasiveness, functional informationand lack of ionizing radiation. Furthermore, recent developments of MRI have led to improved spatial and temporal resolution as well as decreased motion artifacts. Inthis article we describe the technical aspects of gastroin-testinal MRI and present a practical approach for a well-known spectrum of gastrointestinal disease processes.展开更多
Objectives:To retrospectively analyze the clinical results of the treatment of pulmonary multifocal adenocarcinoma presenting as ground glass opacity(GGO)by surgery and thermal ablation.Methods:87 GGO-type pulmonary a...Objectives:To retrospectively analyze the clinical results of the treatment of pulmonary multifocal adenocarcinoma presenting as ground glass opacity(GGO)by surgery and thermal ablation.Methods:87 GGO-type pulmonary adenocarcinomas of 48 patients(14 males and 34 females;mean age:59.7 years old±9.9,range:33-79 years old)had been treated from March 2015 to March 2019.Treatment means included 43 wedge resections,7 segmentectomy,17 lobectomies,and 20 thermal ablations.The indication selected for treatment means,safety,and local tumor progression rate were evaluated.Results:No operation-related death occurred in all patients.42 times of surgery were performed and 67 carcinomas were resected in 42 patients.23 times of single-port Video-assisted thoracoscopic surgery(VATS),8 times of two-port VATS and 11 times of three-port VATS were performed in total.There were 2 cases of air leak(exceeding 1 week),1 case of chylothorax and 1 case of massive pleural effusion.Time duration of surgery was between 60 and 300 mins(mean:167 mins).Intraoperative blood loss was between 5 and 300 mL(mean:44 mL).Time of chest drainage was between 2 and 23 d(mean 4.9 d).Chest drainage volume was between 14 and 4633 mL(mean:872 mL).Post-operation LOS(length of stay)was between 3 and 25 d(mean:6.2 d).15 times of thermal ablation were performed(1 case of air leak)and 20 carcinomas were ablated in 14 patients.The ablation time was between 30 and 120 min(mean:43 min);post-operation LOS was between 1 and 10 d(mean:3.5 d).During the mean follow-up period(16 months±13)(range:5-60 months),no local tumor progression occurred.Conclusions:Surgery and thermal ablation are safe and effective options for the treatment of pulmonary multifocal GGO-type adenocarcinoma.展开更多
物种是生物多样性的基本单元,生殖隔离被认为是物种形成的关键;然而物种并不是静止的而是处于不断的分化演变之中,已经稳定成型但尚未到达分化后期的物种可能存在不完全的生殖隔离。对于物种的认识不能单从某一侧面或局部特征来界定,而...物种是生物多样性的基本单元,生殖隔离被认为是物种形成的关键;然而物种并不是静止的而是处于不断的分化演变之中,已经稳定成型但尚未到达分化后期的物种可能存在不完全的生殖隔离。对于物种的认识不能单从某一侧面或局部特征来界定,而应通过"整合物种概念"来确定物种地位。Flora of China记载了中国产白桫椤属(Sphaeropteris)2种,即白桫椤(S.brunoniana)和笔筒树(S.lepifera),并认为原产中国海南的海南白桫椤(S.hainanensis)和白桫椤为同一物种而将其并入白桫椤;但海南白桫椤在形态上已出现了分化。为探讨白桫椤及其近缘物种的亲缘关系和物种多样性分化的情况,本文采集到9个居群共21个样本,通过GBS简化基因组测序技术获得单核苷酸变异位点(SNP),进行系统发育树的构建和主成分及遗传结构的分析,并结合叶片数量性状的统计分析和孢子形态的观察测量。结果表明,海南白桫椤不仅与云南产白桫椤的基因型不同,且在叶片特征和孢子纹饰上有明显差异;但两个居群的生殖隔离较弱,在广西沿海地区形成杂交产物,其叶片特征为亲本的中间类型。因此,我们认为海南白桫椤是由于地理隔离而形成的一个处在分化路上的物种,建议恢复其物种地位;广西产白桫椤为自然杂交群体,应另处理为独立的自然杂交分类群--广西白桫椤(S. brunoniana×hainanensis)。展开更多
理解物种的濒危机制对生物多样性的科学保护至关重要。荷叶铁线蕨(Adiantum nelumboides)作为国家一级重点保护野生植物,其遗传多样性状况和濒危机制一直存在较大争议。本文利用简化基因组测序技术(genotyping by sequencing, GBS)对来...理解物种的濒危机制对生物多样性的科学保护至关重要。荷叶铁线蕨(Adiantum nelumboides)作为国家一级重点保护野生植物,其遗传多样性状况和濒危机制一直存在较大争议。本文利用简化基因组测序技术(genotyping by sequencing, GBS)对来自6个居群的28个荷叶铁线蕨样本测序,共获得29.6Gb的数据,并筛选得到9,423个高质量单核苷酸变异位点(SNP),通过遗传多样性和居群遗传结构分析,并结合不同气候情景下物种潜在分布区差异,探讨了荷叶铁线蕨的濒危原因和科学保护策略。结果表明:(1)荷叶铁线蕨具有较低的遗传多样性(H_(o)=0.138、H_(e)=0.232、P_(i)=0.373),同时种群间具有较低的遗传分化(F_(st)=0.0202)和基因流(N_(m)=1.9613);(2)所有样本均来自2个遗传分组,基因组大小为5.01-5.83Gb,且均为四倍体,GC含量约为39%-41%;(3)生态位模拟表明,与现代气候相比,在未来气候变化下荷叶铁线蕨的潜在分布区面积略有增加,但高适生区面积减小。其主要适生区向北迁移,影响其分布的主导因子为昼夜温差月均值和最冷季降水量。正是由于荷叶铁线蕨遗传多样性低,不同种群间遗传分化较低,再加上气候条件的变化,其适生区狭窄,导致其遗传多样性和种群数量急剧下降。因此,自身更新能力低以及过度的人为活动干扰可能是导致其濒危的主要原因。建议加强对荷叶铁线蕨的就地保护;通过生境恢复及自然回归等措施,增加居群间的基因交流,防止遗传资源丢失加剧。展开更多
Purpose In X-ray CT systems,ring artifacts caused by the nonuniform response of detector elements degrades the reconstruction quality and affects the subsequent processing and quantitative analysis of the image.Method...Purpose In X-ray CT systems,ring artifacts caused by the nonuniform response of detector elements degrades the reconstruction quality and affects the subsequent processing and quantitative analysis of the image.Method In this paper,a novel method is proposed to remove the ring artifacts in CT image by applying deep learning algorithm based on convolutional neural network(CNN)and recurrent neural network(RNN).First,the reconstructed CT images is transformed into polar coordinate system to make rings appear as stripes.Then,a CNN is constructed to detect the stripes,and a RNN is utilized to process the line artifact correction.After that,by retransforming the corrected image from polar coordinate system to Cartesian coordinate system,a ring artifact removal image can be achieved.Results The presented method can successfully reduce the CT ring artifact on simulated and real data.Specifically,in the experiment with real water phantom,the center and peripheral standard deviations reduced 46%and 24%,respectively.Conclusions The proposed method is potential to be widely deployed in industrial and medical CT systems,due to the excellent results on correction and the real-time performance without adjusting parameters manually.展开更多
Purpose A major challenge for the material decomposition task of the dual-energy computed tomography(DECT)is the algorithm often suffers from heavy noise in the results.The purpose of this study is to propose a scheme...Purpose A major challenge for the material decomposition task of the dual-energy computed tomography(DECT)is the algorithm often suffers from heavy noise in the results.The purpose of this study is to propose a scheme to increase the noise performance of material decomposition.Methods The scheme we propose in this paper is to apply an autoencoder-based denoising procedure to the photon-counting DECT images before they are fed into the material decomposition algorithm.We implement the autoencoder(AE)by stacking a series of convolutional and deconvolutional layers.The decomposition technique adopted in our work is an iterative method using least squares estimation with the Huber loss function.The noises of the input and the output of material decomposition are analyzed with both simulated data and real data.Phantom and chicken wing experiments are conducted with a photoncounting-based spectral CT scanner to evaluate the proposed material decomposition scheme.Results The noise analysis of the input and the output of material decomposition demonstrates a positive correlation between them.Comparative experiment indicates a noise reduction in the output density maps for 26.07%to 35.65%after the autoencoder pre-processing is applied.The resultant contrast-to-noise ratio is largely increased,correspondingly.Conclusions By utilizing the additional autoencoder denoising step,the material decomposition algorithm achieves an improvement in the noise performance of the resultant density maps.展开更多
文摘1概述肺癌是最常见的恶性肿瘤之一,在世界各地,肺癌均居恶性肿瘤死亡构成比的第一位,其发病率和死亡率仍在不断升高。据世界卫生组织（World Health Organization,WHO）下属的国际癌症研究机构（International Agency for Research on Cancer,IARC）出版的GLOBOCAN 2012估计：全世界肺癌新发病例1 8 2.5万（男性124.2万,女性58.3万）.
文摘Over the past two decades, advances in cross-sectionalimaging such as computed tomography and magneticresonance imaging(MRI) have dramatically changed theconcept of gastrointestinal imaging. MR is playing anincreasing role in the evaluation of gastrointestinal disorders. MRI combines the advantages of excellent soft-tissue contrast, noninvasiveness, functional informationand lack of ionizing radiation. Furthermore, recent developments of MRI have led to improved spatial and temporal resolution as well as decreased motion artifacts. Inthis article we describe the technical aspects of gastroin-testinal MRI and present a practical approach for a well-known spectrum of gastrointestinal disease processes.
文摘Objectives:To retrospectively analyze the clinical results of the treatment of pulmonary multifocal adenocarcinoma presenting as ground glass opacity(GGO)by surgery and thermal ablation.Methods:87 GGO-type pulmonary adenocarcinomas of 48 patients(14 males and 34 females;mean age:59.7 years old±9.9,range:33-79 years old)had been treated from March 2015 to March 2019.Treatment means included 43 wedge resections,7 segmentectomy,17 lobectomies,and 20 thermal ablations.The indication selected for treatment means,safety,and local tumor progression rate were evaluated.Results:No operation-related death occurred in all patients.42 times of surgery were performed and 67 carcinomas were resected in 42 patients.23 times of single-port Video-assisted thoracoscopic surgery(VATS),8 times of two-port VATS and 11 times of three-port VATS were performed in total.There were 2 cases of air leak(exceeding 1 week),1 case of chylothorax and 1 case of massive pleural effusion.Time duration of surgery was between 60 and 300 mins(mean:167 mins).Intraoperative blood loss was between 5 and 300 mL(mean:44 mL).Time of chest drainage was between 2 and 23 d(mean 4.9 d).Chest drainage volume was between 14 and 4633 mL(mean:872 mL).Post-operation LOS(length of stay)was between 3 and 25 d(mean:6.2 d).15 times of thermal ablation were performed(1 case of air leak)and 20 carcinomas were ablated in 14 patients.The ablation time was between 30 and 120 min(mean:43 min);post-operation LOS was between 1 and 10 d(mean:3.5 d).During the mean follow-up period(16 months±13)(range:5-60 months),no local tumor progression occurred.Conclusions:Surgery and thermal ablation are safe and effective options for the treatment of pulmonary multifocal GGO-type adenocarcinoma.
文摘物种是生物多样性的基本单元,生殖隔离被认为是物种形成的关键;然而物种并不是静止的而是处于不断的分化演变之中,已经稳定成型但尚未到达分化后期的物种可能存在不完全的生殖隔离。对于物种的认识不能单从某一侧面或局部特征来界定,而应通过"整合物种概念"来确定物种地位。Flora of China记载了中国产白桫椤属(Sphaeropteris)2种,即白桫椤(S.brunoniana)和笔筒树(S.lepifera),并认为原产中国海南的海南白桫椤(S.hainanensis)和白桫椤为同一物种而将其并入白桫椤;但海南白桫椤在形态上已出现了分化。为探讨白桫椤及其近缘物种的亲缘关系和物种多样性分化的情况,本文采集到9个居群共21个样本,通过GBS简化基因组测序技术获得单核苷酸变异位点(SNP),进行系统发育树的构建和主成分及遗传结构的分析,并结合叶片数量性状的统计分析和孢子形态的观察测量。结果表明,海南白桫椤不仅与云南产白桫椤的基因型不同,且在叶片特征和孢子纹饰上有明显差异;但两个居群的生殖隔离较弱,在广西沿海地区形成杂交产物,其叶片特征为亲本的中间类型。因此,我们认为海南白桫椤是由于地理隔离而形成的一个处在分化路上的物种,建议恢复其物种地位;广西产白桫椤为自然杂交群体,应另处理为独立的自然杂交分类群--广西白桫椤(S. brunoniana×hainanensis)。
文摘理解物种的濒危机制对生物多样性的科学保护至关重要。荷叶铁线蕨(Adiantum nelumboides)作为国家一级重点保护野生植物,其遗传多样性状况和濒危机制一直存在较大争议。本文利用简化基因组测序技术(genotyping by sequencing, GBS)对来自6个居群的28个荷叶铁线蕨样本测序,共获得29.6Gb的数据,并筛选得到9,423个高质量单核苷酸变异位点(SNP),通过遗传多样性和居群遗传结构分析,并结合不同气候情景下物种潜在分布区差异,探讨了荷叶铁线蕨的濒危原因和科学保护策略。结果表明:(1)荷叶铁线蕨具有较低的遗传多样性(H_(o)=0.138、H_(e)=0.232、P_(i)=0.373),同时种群间具有较低的遗传分化(F_(st)=0.0202)和基因流(N_(m)=1.9613);(2)所有样本均来自2个遗传分组,基因组大小为5.01-5.83Gb,且均为四倍体,GC含量约为39%-41%;(3)生态位模拟表明,与现代气候相比,在未来气候变化下荷叶铁线蕨的潜在分布区面积略有增加,但高适生区面积减小。其主要适生区向北迁移,影响其分布的主导因子为昼夜温差月均值和最冷季降水量。正是由于荷叶铁线蕨遗传多样性低,不同种群间遗传分化较低,再加上气候条件的变化,其适生区狭窄,导致其遗传多样性和种群数量急剧下降。因此,自身更新能力低以及过度的人为活动干扰可能是导致其濒危的主要原因。建议加强对荷叶铁线蕨的就地保护;通过生境恢复及自然回归等措施,增加居群间的基因交流,防止遗传资源丢失加剧。
基金This work is partially supported by National Key R&D Program of China(No.2017YFF0107201)CAS Inter-disciplinary Innovation Team(No.JCTD-2019-02)+2 种基金National Natural Science Foundation of China(NSFC)(No.11975250)the Science and Technology Service Network Initiative of Chinese Academy of Sciences(No.KFJ-STS-QYZD-193)the Key Technology Research and Development Team Project of Chinese Academy of Sciences(No.GJJSTD20200004).
文摘Purpose In X-ray CT systems,ring artifacts caused by the nonuniform response of detector elements degrades the reconstruction quality and affects the subsequent processing and quantitative analysis of the image.Method In this paper,a novel method is proposed to remove the ring artifacts in CT image by applying deep learning algorithm based on convolutional neural network(CNN)and recurrent neural network(RNN).First,the reconstructed CT images is transformed into polar coordinate system to make rings appear as stripes.Then,a CNN is constructed to detect the stripes,and a RNN is utilized to process the line artifact correction.After that,by retransforming the corrected image from polar coordinate system to Cartesian coordinate system,a ring artifact removal image can be achieved.Results The presented method can successfully reduce the CT ring artifact on simulated and real data.Specifically,in the experiment with real water phantom,the center and peripheral standard deviations reduced 46%and 24%,respectively.Conclusions The proposed method is potential to be widely deployed in industrial and medical CT systems,due to the excellent results on correction and the real-time performance without adjusting parameters manually.
基金the National Key R&D Program of China(Grant No.2016YFC0100400)the Instrument Developing Project of the Chinese Academy of Sciences(Grant No.YZ201511)the Key Technology Research and Development Team Project of Chinese Academy of Sciences(Grant No.GJJSTD2017005).
文摘Purpose A major challenge for the material decomposition task of the dual-energy computed tomography(DECT)is the algorithm often suffers from heavy noise in the results.The purpose of this study is to propose a scheme to increase the noise performance of material decomposition.Methods The scheme we propose in this paper is to apply an autoencoder-based denoising procedure to the photon-counting DECT images before they are fed into the material decomposition algorithm.We implement the autoencoder(AE)by stacking a series of convolutional and deconvolutional layers.The decomposition technique adopted in our work is an iterative method using least squares estimation with the Huber loss function.The noises of the input and the output of material decomposition are analyzed with both simulated data and real data.Phantom and chicken wing experiments are conducted with a photoncounting-based spectral CT scanner to evaluate the proposed material decomposition scheme.Results The noise analysis of the input and the output of material decomposition demonstrates a positive correlation between them.Comparative experiment indicates a noise reduction in the output density maps for 26.07%to 35.65%after the autoencoder pre-processing is applied.The resultant contrast-to-noise ratio is largely increased,correspondingly.Conclusions By utilizing the additional autoencoder denoising step,the material decomposition algorithm achieves an improvement in the noise performance of the resultant density maps.
