Object information based interactive segmentation for fatty tissue extraction

Zhi Guo Zhou, Fang Liu, Li Cheng Jiao, Ling Ling Li, Xiao Dong Wang, Shui Ping Gou, Shuang Wang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1462-1470
Number of pages9
JournalComputers in Biology and Medicine
Issue number10
StatePublished - Oct 1 2013


  • Fatty tissue
  • Gastric cancer
  • Interactive image segmentation
  • Mean shift
  • Object information

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications


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