首页> 外国专利> DIFFERENTIAL DIAGNOSTIC TECHNIQUE FOR FOLLICULAR ADENOMA AND FOLLICULAR THYROID CARCINOMA

DIFFERENTIAL DIAGNOSTIC TECHNIQUE FOR FOLLICULAR ADENOMA AND FOLLICULAR THYROID CARCINOMA

机译:滤泡性腺瘤和滤泡性甲状腺癌的鉴别诊断技术

摘要

FIELD: medicine.;SUBSTANCE: invention refers to medicine, particularly to oncology, and can be used for differential diagnostics of follicular adenoma and follicular thyroid carcinoma. Thyrocele material is sampled by aspiration fine-needle puncture and/or tumour tissue scrapping; the tumour smears are prepared for the cytological analysis; digital images of the tumour smears are made by the image analysis system comprising the incident light microscope, the digital video camera, the computer and the image processor; the digital images are analysed by double-layer computer neural-net program pre-learned to recognise follicular thyroid carcinoma and adenoma from the master images of the smears histologically diagnosed. Herewith the original digital images of the tumour smears are made at 400-power microscope magnification and resolution 1388×1040 pixels. The original images are downsised to 256×256 pixels within space frequency range 1-128 relative units with using the computer program incorporating the pre-processor. Fourier analysis of the original images enables for automatic convert imaging within space frequency range 96-128 relative units to be used for the further analysis. Each master image of the learning sample is associated with the first layer neuron; in convert image space, the first layer neurons estimate Euclidean distance between each master image of the learning sample and the test image. Herewith derived estimations are assigned with an appropriate positive or negative sign regarding the tumour class (type) of the master image. Minimal Euclidean distance between the master and test image indicate the gainer among the first layer neurons in each of two classes; the only second layer neuron ensures summarising reciprocal Euclidean distances with the related sign within the gain groups. By comparing the total to the limit, the class of the tested image corresponding to follicular adenoma or follicular thyroid carcinoma is specified.;EFFECT: improved diagnostic objectivity and elimination of its dependence on insufficient skills.;1 tbl, 1 ex
机译:技术领域本发明涉及药物,特别是涉及肿瘤学,并且可以用于滤泡性腺瘤和滤泡性甲状腺癌的鉴别诊断。通过抽吸细针穿刺和/或刮除肿瘤组织取样甲状腺肿物质。准备好肿瘤涂片以进行细胞学分析;肿瘤涂片的数字图像由图像分析系统制成,该系统包括入射光显微镜,数字摄像机,计算机和图像处理器。通过双层计算机神经网络程序对数字图像进行分析,该程序预先学习以从组织学诊断的涂片主图像中识别滤泡状甲状腺癌和腺瘤。在此,以400倍的显微镜放大倍数和分辨率1388×1040像素制作了肿瘤涂片的原始数字图像。使用包含预处理器的计算机程序,可以在空间频率范围1-128相对单位内将原始图像缩小为256×256像素。原始图像的傅里叶分析可以在空间频率范围96-128个相对单位内自动转换成像,以用于进一步分析。学习样本的每个主图像都与第一层神经元相关。在转换图像空间中,第一层神经元估计学习样本的每个主图像与测试图像之间的欧几里得距离。因此,派生的估计值将分配有关主图像肿瘤类别(类型)的适当正号或负号。主图像和测试图像之间的最小欧几里得距离指示两类中的每一类的第一层神经元之间的增益。唯一的第二层神经元可确保在增益组内汇总相互的欧几里得距离和相关的符号。通过将总数与极限值进行比较,指定了与滤泡性腺瘤或滤泡性甲状腺癌相对应的测试图像的类别。效果:提高了诊断的客观性并消除了其对技能不足的依赖性。1tbl,1 ex

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