Vijayakumar C, Gharpure Damayanti Chandrashekhar
Department of Radiodiagnosis and Imaging, Armed Forces Medical College, Pune, Maharashtra, India.
J Med Phys. 2011 Jul;36(3):147-58. doi: 10.4103/0971-6203.83481.
Most of the commercially available software for brain tumor segmentation have limited functionality and frequently lack the careful validation that is required for clinical studies. We have developed an image-analysis software package called 'Prometheus,' which performs neural system-based segmentation operations on MR images using pre-trained information. The software also has the capability to improve its segmentation performance by using the training module of the neural system. The aim of this article is to present the design and modules of this software. The segmentation module of Prometheus can be used primarily for image analysis in MR images. Prometheus was validated against manual segmentation by a radiologist and its mean sensitivity and specificity was found to be 85.71±4.89% and 93.2±2.87%, respectively. Similarly, the mean segmentation accuracy and mean correspondence ratio was found to be 92.35±3.37% and 0.78±0.046, respectively.
大多数市售的脑肿瘤分割软件功能有限，且常常缺乏临床研究所需的严格验证。我们开发了一个名为“普罗米修斯”的图像分析软件包，它利用预训练信息对磁共振成像（MR图像）执行基于神经系统的分割操作。该软件还能够通过使用神经系统的训练模块来提高其分割性能。本文的目的是介绍该软件的设计和模块。普罗米修斯的分割模块主要可用于MR图像的分析。通过与放射科医生的手动分割进行对比验证，发现普罗米修斯的平均灵敏度和特异性分别为85.71±4.89%和93.2±2.87%。同样，平均分割准确率和平均对应率分别为92.35±3.37%和0.78±0.046。
