Abstract—Image segmentation plays a crucial role in many medical imaging applications by extracting the regions of interest. Accurate segmentation of medical images is a key step in the use of computer-aided diagnosis (CAD) systems to improve the sensitivity and specificity of lesion detection. In this paper, segmentation problems in medical imaging modalities especially for lung CT as well as for thyroid ultrasound (US) are discussed along with their comparative results are shown using automatic tools as well as with some specific algorithms. In this paper various automatic tools as well as manual segmentation algorithms have been used and compared. Both the outcomes either from automatic tool as well as using an algorithm provide the required ROI (region of interest) but automatic tool’s output is more efficient and perfect. 3D visualization as well as volumetric segmentation is done accurately with the help of these tools which help in segmenting CT (3D) images especially.
Index Terms—CT, US, Region of Interest (ROI), Interstitial Lung Disease (ILD).
Cite: Sonali Bhadoria, Preeti Aggarwal, C. G. Dethe, and Renu Vig, "Comparison of Segmentation Tools for Multiple Modalities in Medical Imaging," Journal of Advances in Information Technology, Vol. 3, No. 4, pp. 197-205, November, 2012.doi:10.4304/jait.3.4.197-205
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