Question

跪求英文高手，翻译下面三段话，如果采纳可以再加分哦，关键是翻译不能中式化

近年来，图像分割在医学图像领域的应用起到至关重要的作用。利用计算机技术对宫颈细胞进行定量分析在宫颈癌和癌前病变的辅助诊断具有重大意义。由于宫颈细胞涂片制作的差异性、细胞重叠、细胞样本噪声等原因，使得细胞分割非常有难度。
本文在前人研究成果的基础上，采用最大类方差法、最佳直方图熵法结合遗传算法(GA)实现宫颈细胞的分割，然后对这些分割后的细胞进行特征提取，最后利用Delphi设计宫颈癌细胞特征显示系统，直观展现分割效果。本课题内容主要涉及三个方面：对宫颈细胞样本进行预处理后，利用自适应最大类方差法，实现细胞与背景的分离。以灰度图像的最大熵作为适度函数，将图像分割问题转变为优化问题。利用遗传算法寻优高效性，获取最佳阈值，从而实现细胞核与细胞的有效分割；在此基础之上，提取有助于宫颈癌辅助诊断的20个特征，其中包括几何特征和光密度特征；最后，以Access为数据库管理系统，使用Delphi进行应用程序的开发，设计出宫颈癌细胞特征显示系统。本系统包括信息查询、添加新病人和写报告三个模块。
实验结果表明，本文采用的分割算法效果显著，特别是最佳直方图熵法与遗传算法结合后，与传统的遗传算法相比，不仅提高算法的寻优能力，而且大大缩短了寻找阈值时间，且细胞图像分割效果非常好。宫颈癌细胞特征显示系统的设计大大降低医务工作人员的劳动强度，从而可以减小疾病的误判率，同时为宫颈细胞自动分析系统的开发奠定了基础。

Answer 1

In recent years, image segmentation in medical image application plays an important role in. Using computer technique to quantitative analysis of cervical cells in cervical cancer and precancerous lesions of the aided diagnosis is of great significance. As a result of cervical smear making differences, cell overlap, cell sample noise and other reasons, makes the cell segmentation is very difficult.In this paper, on the basis of previous research results, using the maximum variance method, optimal histogram entropy method with genetic algorithm ( GA ) for cervical cell segmentation, and then the segmentation of cells after feature extraction, the final design based on Delphi cervical cancer cells showed characteristic system, visual display segmentation effect. This topic mainly involves three aspects: on cervical cell samples were pretreated, using adaptive maximum variance method, realization of cells and background. The gray image of the maximum entropy as the fitness function, image segmentation problem into an optimization problem. The use of genetic algorithm optimization efficiency, obtain the optimal threshold, thereby realizing the nucleus and cell segmentation; on this basis, the extraction contribute to cervical cancer assistant diagnosis of 20 features, including geometric and densitometric features; finally, taking Access as the database management system, using Delphi application development, design of cervical cancer cells feature display system. The system includes the information query, add new patients and report writing three modules.The experimental results show that, the segmentation effect is remarkable, especially the optimal histogram entropy method with genetic algorithm combined with traditional genetic algorithm, compared, not only improve the searching capability of the algorithm, but also greatly shorten the time for cell image segmentation threshold, and the effect is very good. Cervical cancer cell characteristics display system design can greatly reduce the labor intensity of the medical staff, thereby reducing the error rate for both diseases, cervical cell automatic analysis system for the development of the foundation.

Answer 2

In recent years, image segmentation in medical image application plays an important role in. Using computer technique to quantitative analysis of cervical cells in cervical cancer and precancerous lesions of the aided diagnosis is of great significance. As a result of cervical smear making differences, cell overlap, cell sample noise and other reasons, makes the cell segmentation is very difficult.

In this paper, on the basis of previous research results, using the maximum variance method, optimal histogram entropy method with genetic algorithm ( GA ) for cervical cell segmentation, and then the segmentation of cells after feature extraction, the final design based on Delphi cervical cancer cells showed characteristic system, visual display segmentation effect. This topic mainly involves three aspects: on cervical cell samples were pretreated, using adaptive maximum variance method, realization of cells and background. The gray image of the maximum entropy as the fitness function, image segmentation problem into an optimization problem. The use of genetic algorithm optimization efficiency, obtain the optimal threshold, thereby realizing the nucleus and cell segmentation; on this basis, the extraction contribute to cervical cancer assistant diagnosis of 20 features, including geometric and densitometric features; finally, taking Access as the database management system, using Delphi application development, design of cervical cancer cells feature display system. The system includes the information query, add new patients and report writing three modules.

The experimental results show that, the segmentation effect is remarkable, especially the optimal histogram entropy method with genetic algorithm combined with traditional genetic algorithm, compared, not only improve the searching capability of the algorithm, but also greatly shorten the time for cell image segmentation threshold, and the effect is very good. Cervical cancer cell characteristics display system design can greatly reduce the labor intensity of the medical staff, thereby reducing the error rate for both diseases, cervical cell automatic analysis system for the development of the foundation. 望采纳

Answer 3

In recent years, the image segmentation in medical image application in the field of play a crucial role. Using the computer technology to cervical cells for quantitative analysis in cervical cancer and pre-cancerous assistant diagnosis is of great significance. Due to the differences of cervical cells smear production, cell overlap, cell samples noise wait for a reason, so that the cell division is very difficult.

Based on the previous research results, and on the basis of the largest categories using variance method, the best of histogram entropy with genetic algorithm (GA) to implement cervical cells division, then on to the division of cells after feature extraction, finally using Delphi design cervical cancer cells characteristic display system, intuitive show segmentation result. This subject mainly on three aspects: cervical cells to sample pretreatment, the largest categories of the adaptive variance method, realize the separation of cells and background. The maximum entropy with gray image as a moderate function, the image segmentation problem change for optimization problems. By using the genetic algorithm optimal efficiency, obtain optimal threshold value, so as to realize the effective segmentation and the cell nucleus; Based on this, the extraction of cervical cancer diagnosis of auxiliary to 20 features, including geometric features and light density characteristics; Finally, the paper takes Access to database management system, using Delphi for application development, design the cervical cancer cells features the display system. This system includes information query, add new patients and writing the report three modules.

The experimental results show that, this article USES the segmentation algorithm effect is remarkable, especially the best of histogram entropy and the genetic algorithm combining with the traditional genetic algorithm, the algorithm not only improve the optimization ability, and greatly shorten the time looking for threshold, and cell image segmentation effect is very good. Cervical cancer cells that the design of the system characteristics greatly reduce the labor intensity of the medical staff, which can reduce the disease afr, at the same time for cervical cells to be automatic analysis system development laid a foundation.