Tsai Yi-Fen, Chiang I-J, Lee Yeng-Chi, Liao Chun-Chih, Wang Kao-Lung
Graduate Institute of Medical Informatics, Taipei Medical University.
Conf Proc IEEE Eng Med Biol Soc. 2005;2005:3074-7. doi: 10.1109/IEMBS.2005.1617124.
With the advancement of the imaging facility and image processing technique, computer assisted surgical planning and image guided technology have become increasingly used in neurosurgery. For MRI has the characteristic of multi-spectral image data., so knowledge-base techniques is widely used in brain MRI segmentation. Here we recognize the location of the tumor automatically and provide an accurate result by Estimation Maximization method. Simultaneously, promote the efficiency of reading image as well.
随着成像设备和图像处理技术的进步，计算机辅助手术规划和图像引导技术在神经外科中的应用越来越广泛。由于MRI具有多光谱图像数据的特点，因此基于知识的技术被广泛应用于脑MRI分割。在这里，我们通过期望最大化方法自动识别肿瘤的位置并提供准确的结果。同时，也提高了图像读取的效率。
