An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-ste...An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-step converter consisting of a 6-bit coarse quantization and a 6-bit fine quantization,which supports a time resolution of 120 ps and multiphoton counting up to 2 GHz without a GHz reference frequency.The proposed hTDC is designed in 0.11μm CMOS process with an area consumption of 6900μm^(2).The data from a behavioral-level model is imported into the designed hTDC circuit for simulation verification.The post-simulation results show that the proposed hTDC achieves 0.8%depth precision in 9 m range for short-range system design specifications and 0.2%depth precision in 48 m range for long-range system design specifications.Under 30×10^(3) lux background light conditions,the proposed hTDC can be used for SPAD-based flash LiDAR sensor to achieve a frame rate to 40 fps with 200 ps resolution in 9 m range.展开更多
基金National Key Research and Development Program of China(2022YFB2804401)。
文摘An in-pixel histogramming time-to-digital converter(hTDC)based on octonary search and 4-tap phase detection is presented,aiming to improve frame rate while ensuring high precicion.The proposed hTDC is a 12-bit two-step converter consisting of a 6-bit coarse quantization and a 6-bit fine quantization,which supports a time resolution of 120 ps and multiphoton counting up to 2 GHz without a GHz reference frequency.The proposed hTDC is designed in 0.11μm CMOS process with an area consumption of 6900μm^(2).The data from a behavioral-level model is imported into the designed hTDC circuit for simulation verification.The post-simulation results show that the proposed hTDC achieves 0.8%depth precision in 9 m range for short-range system design specifications and 0.2%depth precision in 48 m range for long-range system design specifications.Under 30×10^(3) lux background light conditions,the proposed hTDC can be used for SPAD-based flash LiDAR sensor to achieve a frame rate to 40 fps with 200 ps resolution in 9 m range.
文摘目的 探讨基于动态对比增强磁共振成像(dynamic contrast enhancement magnetic resonance imaging,DCE-MRI)药代动力学参数直方图特征预测前列腺癌(prostate cancer,PCa)内分泌治疗反应的价值。材料与方法 回顾性分析2018年1月至2023年10月河西学院附属张掖人民医院(中心1)和2020年2月至2023年2月甘肃省人民医院(中心2)PCa患者在内分泌治疗前2周的临床、影像资料,将中心1收集的105例病例按7∶3的比例分为训练集(73例)和内部验证集(32例),将中心2收集的47例病例作为外部验证集。选取DCE-MRI原始图像,通过Siemens Syngo.via工作站获得药代动力学参数容积转运常数(volume transfer contrast,Ktrans)、速率常数(rate contrast,Kep)、血管外细胞外容积分数(extravascular extracellular volume fraction,Ve)伪彩图。在3D Slicer软件中参照轴位T2WI在药代动力学参数伪彩图上逐层勾画全前列腺腺体感兴趣区(region of interest,ROI)后提取直方图特征,经最小绝对收缩和选择算子(least absolute shrinkage and selection operator,LASSO)降维筛选出8个最优特征并计算直方图特征。采用单因素及后向多因素logistic回归分析内分泌治疗反应良好组和不良组的独立预测因素,并构建临床模型、直方图特征模型、联合模型。采用受试者工作特性曲线、校准曲线和决策曲线评价模型的效能,通过DeLong检验评估各模型曲线下面积(area under the curve,AUC),最后基于联合模型的独立预测因素绘制列线图。结果 训练集、内部验证集和外部验证集中治疗反应良好组和不良组之间Gleason评分、MRI-T分期、直方图特征差异均存在统计学意义(P<0.001)。后向多因素logistic回归分析显示Gleason评分(OR=0.925,95%CI:0.859~0.958,P=0.038)、MRI-T分期(OR=0.871,95%CI:0.800~0.949,P=0.002)及直方图特征(OR=0.096,95%CI:0.056~0.137,P<0.001)是PCa内分泌治疗反应的独立预测因素;临床模型在训练集、内部验证集及外部验证集的AUC分别为0.857(95%CI:0.774~0.939)、0.953(95%CI:0.888~0.996)、0.808(95%CI:0.676~0.941);直方图特征模型在训练集、内部验证集及外部验证集的AUC为0.874(95%CI:0.769~0.951)、0.816(95%CI:0.664~0.967)、0.674(95%CI:0.517~0.831);联合模型在训练集、内部验证集及外部验证集的AUC为0.951(95%CI:0.906~0.994)、0.973(95%CI:0.922~0.995)、0.830(95%CI:0.699~0.960);决策曲线和校准曲线分析表明,联合模型具有良好的临床应用价值和稳定性;DeLong检验及NRI值显示联合模型的预测效能优于临床模型和直方图特征模型。结论 DCE-MRI药代动力学参数直方图特征是预测PCa内分泌治疗反应的独立预测因素,联合模型在预测PCa内分泌治疗反应方面具有较好的价值,为临床治疗决策提供了新的思路。
