Article

Segmentation of lungs from CT scan images for early diagnosis of lung cancer

01/2006;

ABSTRACT

Segmentation is an important step in medical image analysis and classification for radiological evaluation or computer aided diagnosis. The CAD (Computer Aided Diagnosis) of lung CT generally first segment the area of interest (lung) and then analyze the separately obtained area for nodule detection in order to diagnosis the disease. For normal lung, segmentation can be performed by making use of excellent contrast between air and surrounding tissues. However this approach fails when lung is affected by high density pathology. Dense pathologies are present in approximately a fifth of clinical scans, and for computer analysis such as detection and quantification of abnormal areas it is vital that the entire and perfectly lung part of the image is provided and no part, as present in the original image be eradicated. In this paper we have proposed a lung segmentation technique which accurately segment the lung parenchyma from lung CT Scan images. The algorithm was tested against the 25 datasets of different patients received from Ackron Univeristy, USA and AGA Khan Medical University, Karachi, Pakistan.

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Available from: Anwar Mirza
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    • "Based on this high performance, radiologists can easily photograph the whole human chest, abdomen, or torso with high spatial resolution in a one-time CT scan. Multisided CT imaging is the primary digital technique for imaging the lung for the detection of pulmonary (lung) disease such as lung cancer, tumor, and cystic fibrosis [12]. Sometimes doctors recommend the MRI of lung depending upon the patient's condition. "

    Preview · Article · Nov 2012
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    • "Based on this high performance, radiologists can easily photograph the whole human chest, abdomen, or torso with high spatial resolution in a one-time CT scan. Multisided CT imaging is the primary digital technique for imaging the lung for the detection of pulmonary (lung) disease such as lung cancer, tumor, and cystic fibrosis [7]. Sometimes doctors recommend the MRI of lung depending upon the patient's condition. "
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    • "Once the threshold has been selected and applied, region growing and connectivity analysis are used to extract the exact cavity region with accuracy. The interested reader may refer [20] for complete procedure of isolating the lung parenchyma from CT scan image. The overall algorithm for segmentation of the lung parenchyma from the input CT scan image is described as under: 1. Read the input image. "
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