基于MRI数据的胎盘图像分割重建系统设计
Design of Placental Image Segmentation Reconstruction System Based on MRI Data
DOI: 10.12677/orf.2024.142155, PDF,    科研立项经费支持
作者: 储著铭, 李 筠, 杨海马：上海理工大学光电信息与计算机工程学院，上海；刘 瑾, 丁大民：上海工程技术大学电子电气工程学院，上海；付 玏：同济大学医学院上海市第一妇婴保健院，上海
关键词: 深度学习；医学图像处理；三维重建；胎盘；Deep Learning； Medical Image Processing； Three-Dimensional Reconstruction； Placenta
摘要: 本文基于核磁共振图像数据，利用CLAHE算法对图像进行了图像增强，使用改进的深度学习算法实现了胎盘区域的有效分割，并通过光线投射算法进行胎盘的体绘制和移动立方体算法的面绘制，构建出胎盘的可视化模型，最后利用PYQT技术设计了一套胎盘分割与三维重建系统，完成了胎盘MRI数据的读取、预处理、分割、三维重建功能，并加入了一些交互选项，该系统可以方便快捷的对胎盘区域进行有效的分割，同时也可以构建出直观的三维模型，有利于帮助医护人员的快速地进行胎盘相关疾病的诊断。
Abstract: In this paper, based on the data of MRI, image enhancement was performed using CLAHE algorithm, effective segmentation of the placental region was achieved using improved deep learning algorithm, and the visualization model of the placenta was constructed by body drawing of the placenta through light projection algorithm and surface drawing through moving cube algorithm, finally, a set of placenta segmentation and three-dimensional reconstruction was designed by using the PYQT technology. Finally, a placental segmentation and 3D reconstruction system is designed using PYQT technology, which completes the functions of reading, preprocessing, segmentation and 3D reconstruction of placental MRI data, and adds some interactive options. The system can conveniently and quickly segment the placental region effectively, and also constructs an intuitive 3D model, which is conducive to helping healthcare workers to quickly diagnose placenta-related diseases.
文章引用：储著铭, 李筠, 杨海马, 刘瑾, 付玏, 丁大民. 基于MRI数据的胎盘图像分割重建系统设计[J]. 运筹与模糊学, 2024, 14(2): 500-509. https://doi.org/10.12677/orf.2024.142155

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