School of Computer Science and Technology, Xidian University, Xi'an 710071, PR China; Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi'an 710071, PR China.
Comput Biol Med. 2013 Oct;43(10):1462-70. doi: 10.1016/j.compbiomed.2013.07.023. Epub 2013 Aug 2.
Lymph nodes are very important factors for diagnosing gastric cancer in clinical use, and are usually distributed within the fatty tissue around the stomach. When extracting fatty tissues whose structures and textures are complicated, automatic extraction is still a challenging task, while manual extraction is time-consuming. Consequently, semi-automatic extraction, which allows introducing interactive operations, appears to be more realistic. Currently, most interactive methods need to indicate the position and main features in both the object and background. However, it is easier for radiologists to only mark object information. Due to this issue, a new Object Information based Interactive Segmentation (OIIS) method is proposed in this paper. Different from the most existing methods, OIIS just needs to input the object information, while the background information is not required. Experimental results and comparative studies show that OIIS is effective for fatty tissue extraction.
淋巴结是临床医学中诊断胃癌的重要因素，通常分布在胃周围的脂肪组织中。在提取结构和纹理复杂的脂肪组织时，自动提取仍然是一项具有挑战性的任务，而手动提取则很耗时。因此，允许引入交互操作的半自动提取似乎更为现实。目前，大多数交互式方法需要在对象和背景中都指示位置和主要特征。然而，放射科医生只标记对象信息更为容易。由于这个问题，本文提出了一种新的基于对象信息的交互式分割（OIIS）方法。与大多数现有的方法不同，OIIS 只需要输入对象信息，而不需要背景信息。实验结果和比较研究表明，OIIS 对脂肪组织提取是有效的。
