Document Citation

Title:
Graph Cut Based Automatic Lung Boundary Detection In Chest Radiographs.

Author(s):
Sema Candemir, Stefan Jaeger, Kannappan Palaniappan1, Sameer Antani, and George Thoma.

Institution(s):
1) National Library of Medicine, Bethesda, MD 20894

Source:
1st Annual IEEE Healthcare Innovation Conference of the IEEE EMBS. Houston, TX. November 2012:7-9.

Abstract:
The National Library of Medicine (NLM) is developing a digital chest x-ray (CXR) screening system for deployment in resource constrained communities. An important first step in the analysis of digital CXRs is the automatic detection of the lung regions. In this paper, we present a graph cut based robust lung segmentation method that detects the lungs with high accuracy. The method consists of two stages: (i) average lung shape model calculation, and (ii) lung boundary detection based on graph cut. Preliminary results on public chest x-rays demonstrate the robustness of the method.

Publication Type: CONFERENCE

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