Abstract
Image based Lung cancer diagnosis offers an effective and non-intrusive method for identification and diagnosis of lung cancer in a patient. This is done by segmentation of lung nodules from radiological images obtained from patients. This paper proposes a framework to segment nodule lesions in images. The novelty of the proposed framework is that we use optical flow information along with the morphological operations on images. The proposed framework applies the Farneback method of optical flow extraction algorithms for the nodule segmentation task. This work validates and demonstrates that optical flow information is useful for nodule segmentation and can be used in tandom with other features.
This work was carried out at ABV-IIITM Gwalior, India with funding from DST, Govt. of India.
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Suji, R.J., Bhadouria, S.S., Dhar, J., Godfrey, W.W. (2020). Optical Flow Based Background Subtraction Method for Lung Nodule Segmentation. In: Nain, N., Vipparthi, S., Raman, B. (eds) Computer Vision and Image Processing. CVIP 2019. Communications in Computer and Information Science, vol 1147. Springer, Singapore. https://doi.org/10.1007/978-981-15-4015-8_23
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DOI: https://doi.org/10.1007/978-981-15-4015-8_23
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