Image Processing Tool Promoting Decision-Making in Liver Surgery of Patients with Chronic Kidney Disease
Image Processing Tool Promoting Decision-Making in Liver Surgery of Patients with Chronic Kidney Disease作者机构：Department of Electronics and Microelectronics Technical University of Varna Varna Bulgaria Department of Medical Physics University of Patras Patras Greece Department of Radiology Medical University of Varna Varna Bulgaria Department of Surgery Medical University of Varna Varna Bulgaria
出 版 物：《Journal of Software Engineering and Applications》 (软件工程与应用（英文）)
年 卷 期：2014年第7卷第2期
页 面：118-127页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Non-Contrast Enhanced Computed Tomography Images Evaluation of the Residual Function of the Liver Liver Segmentation Seeded Regional Growing Algorithm Virtual Tumor Resection Decision-Making Educational Tool
摘 要：Preoperative assessment of the liver volume and function of the remnant liver is a mandatory prerequisite before performing major hepatectomy. The aim of this work is to develop and test a software application for evaluation of the residual function of the liver prior to the intervention of the surgeons. For this purpose, a complete software platform consisting of three basic modules: liver volume segmentation, visualization, and virtual cutting, was developed and tested. Liver volume segmentation is based on a patient examination with non-contrast abdominal Computed Tomography (CT). The basis of the segmentation is a multiple seeded region growing algorithm adapted for use with CT images without contrast-enhancement. Virtual tumor resection is performed interactively by outlining the liver region on the CT images. The software application then processes the results to produce a three-dimensional (3D) image of the “resected region. Finally, 3D rendering module provides possibility for easy and fast interpretation of the segmentation results. The visual outputs are accompanied with quantitative measures that further provide estimation of the residual liver function and based on them the surgeons could make a better decision. The developed system was tested and verified with twenty abdominal CT patient sets consisting of different numbers of tomographic images. Volumes, obtained by manual tracing of two surgeon experts, showed a mean relative difference of 4.5%. The application was used in a study that demonstrates the need and the added value of such a tool in practice and in education.
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