Dynamic Changes of Renal Function and Urinary Sediment during the Onset of Urolithiasis in Goats

山羊尿石症发生过程中肾功能及 尿 沉渣变化的动态研究

Urinary sediment analysis is one of the most important ways for the diagnosis of urinary organ diseases .

尿 沉渣 成分分析是泌尿系统疾病诊断的主要方法之一。

Segmentation and Recognition of Casts in Urinary Sediment Microscopic Images

尿 沉渣显微图像中的管型分割与识别

Comparative Analysis of Visible Component in Urine Samples by Dry-Chemistry Method and Urinary Sediment Examination

尿干化学分析仪与 尿 沉渣分析仪对尿中有形成分对比分析

Red Blood Cell Detection in Urinary Sediment Images Based on Ellipse Detecting Hough Transform

基于椭圆Hough变换的 尿 沉渣图像红细胞检测

Positiveness of acid-fast stains of urinary sediment and specificity of B-ultrasonography were low .

尿 沉渣找抗酸杆菌阳性率较低，B超检查对 泌尿 系结核感染诊断的特异性较低。

The automatic process of urinary sediment images is commonly divided into segmentation recognition and counting .

市场上已经出现了多种 尿 沉渣 自动 分析仪， 尿 沉渣图像的自动处理通常可分为 有形 成分的分割和识别与计数。

Objective : To investigate the necessity of urinary sediment examination in those that had been analyzed by dry-chemistry method .

目的：探讨尿液干化学分析后进行 尿 沉渣镜检的必要性。

Experiment result shows that the new method is suitable for urinary sediment images auto analysis system .

将本方法应用于 尿 沉渣检查自动图像分析系统中，实验结果表明这一方法效果较好。

Research and implementation of urinary sediment overlapping cells image segmentation based on combination

基于组合的 尿 沉渣粘连细胞分割算法的研究与实现

Significance of detection of urinary sediment RBP NAG and renal pathological biopsy in analysis of acute renal failure

尿 沉渣及尿RBP、NAG检测与急性肾衰肾活检相关性

Contrast analysis of dry urinalysis and urinary sediment microscopy

尿干化学分析与 尿 沉渣镜检的对比分析

It is necessary to correctly segment image in order to analyze accurately urinary sediment visible component .

为了能够对 尿 沉渣有形成分进行准确的数据分析，关键是要对该种图像进行正确分割。

Methods 331 RBC positive urine samples that had been detected by UF-100 automatic urinary sediment analyzer were microscopically re-examined .

方法：对UF-100全自动 尿 沉渣分析仪检测的331例红细胞RBC阳性尿液标本进行复查镜检。

And then using morphology feature parameter analyzes and describes segmented urinary sediment image .

对分割后的 尿 沉渣图像，利用形态特征参数对 尿沉渣 有形 成分进行描述。

HV RNA positive rate in urinary sediment has positive correlation with kidney damage .

尿 沉渣细胞中病毒RNA的检出率与肾脏损伤成正比。

Analysis and exploration of a few problems in urinary sediment examination of 628 cases

628例 尿 沉渣检验中几个问题的分析探讨

The Mathematical Model and Fast Algorithm for Segmentation and Denoising of Urinary Sediment Microscopic Image

尿 沉渣显微细胞图像去噪与分割的数学模型及快速算法

Objective To investigate the sensitivity of two methods ( dry-chemistry urinary sediment examination ) in deteciting the visible components in urine samples .

目的探讨尿干化学分析与 尿 沉渣镜检两种方法对尿中有形成分的敏感性。

Diagnosis of origin of hematuria with UF-100 urinary sediment analyzer

UF-100 尿 沉渣分析仪鉴别血尿来源

The correlativity between UF-100 and the method of urinary sediment quantitative analysis board

UF-100和 尿 沉渣定量分析板法的相关性

The Research of Urinary Sediment Visual Component Analysis Based on Fuzzy Clustering ;

基于模糊聚类的 尿 沉渣有形成分分析研究 酒渣 慢慢 地 沉淀 下来。

Results analysis of urinary cast detected by UF-50 complete automatic urinary sediment analyzer

UF-50全自动 尿 沉渣分析仪检测尿中管型结果的分析

Objective : To investigate the clinical significance of RBC-Information by UF-100 urinary sediment analyzer .

目的：探讨UF&100 尿 沉渣分析仪提示红细胞信息的临床意义。

Clinical significance of UF-1000i Urinary Sediment Analyzer in identification of hematuria

UF-1000i 尿 沉渣分析仪鉴别血尿的临床意义

ObjectiveTo compare the results of urinary sediment analyzer combined urine dry chemistry analyzer and microscopy in urine white and red blood cells .

目的： 尿 沉渣分析仪联合尿干化学分析仪与显微镜镜检测定尿中白细胞和红细胞结果的比较。

Good recognition results were achieved on real-world urinary sediment microscopic images .

在实际图像上获得了 较好的识别效果。

Object To evaluate characters and application in clinic for US-2020 urinary sediment automatic analyzer .

目的评估重庆天海US2020全自动 尿 沉渣分析仪的性能及临床应用。

Observation on Urinary Sediment Smear Staining of Acute Female Urinary System Infection

女性急性泌尿系感染 尿 沉渣涂片染色观察

In view of urinary microscopic image recognition a novel urinary sediment image segmentation approach based on cellular neural network ( CNN ) was presented .

针对临床 尿 沉渣显微图像识别问题，提出了一种新的图像预处理方法和基于细胞神经网络（CNN）的分割算法。