Hamoud Al-Tamimi Mohammed Sabbih, Sulong Ghazali, Shuaib Ibrahim Lutfi
UTM-IRDA Digital Media Centre (MaGIC-X), Faculty of Computing, University Technology Malaysia, 81310 Skudai, Johor Bahru, Malaysia; Department of Higher Studies, University of Baghdad, Al-Jaderia, Baghdad, Iraq.
UTM-IRDA Digital Media Centre (MaGIC-X), Faculty of Computing, University Technology Malaysia, 81310 Skudai, Johor Bahru, Malaysia.
Magn Reson Imaging. 2015 Jul;33(6):787-803. doi: 10.1016/j.mri.2015.03.008. Epub 2015 Apr 9.
Resection of brain tumors is a tricky task in surgery due to its direct influence on the patients' survival rate. Determining the tumor resection extent for its complete information via-à-vis volume and dimensions in pre- and post-operative Magnetic Resonance Images (MRI) requires accurate estimation and comparison. The active contour segmentation technique is used to segment brain tumors on pre-operative MR images using self-developed software. Tumor volume is acquired from its contours via alpha shape theory. The graphical user interface is developed for rendering, visualizing and estimating the volume of a brain tumor. Internet Brain Segmentation Repository dataset (IBSR) is employed to analyze and determine the repeatability and reproducibility of tumor volume. Accuracy of the method is validated by comparing the estimated volume using the proposed method with that of gold-standard. Segmentation by active contour technique is found to be capable of detecting the brain tumor boundaries. Furthermore, the volume description and visualization enable an interactive examination of tumor tissue and its surrounding. Admirable features of our results demonstrate that alpha shape theory in comparison to other existing standard methods is superior for precise volumetric measurement of tumor.
由于脑肿瘤切除术直接影响患者的生存率，因此它是外科手术中一项棘手的任务。通过术前和术后磁共振成像（MRI）确定肿瘤切除范围以获取有关其体积和尺寸的完整信息，需要进行准确的估计和比较。使用自行开发的软件，采用主动轮廓分割技术对术前MR图像上的脑肿瘤进行分割。通过阿尔法形状理论从其轮廓获取肿瘤体积。开发了图形用户界面来渲染、可视化和估计脑肿瘤的体积。使用互联网脑分割库数据集（IBSR）来分析和确定肿瘤体积的可重复性和再现性。通过将使用所提出方法估计的体积与金标准体积进行比较，验证了该方法的准确性。发现通过主动轮廓技术进行的分割能够检测脑肿瘤边界。此外，体积描述和可视化能够对肿瘤组织及其周围环境进行交互式检查。我们结果的出色特征表明，与其他现有标准方法相比，阿尔法形状理论在精确测量肿瘤体积方面更具优势。
