Abstract
Due to the variable shapes of objects, high noise intensity and complex environments, the field of image segmentation still has great challenges. To address these issues, we present a new image segmentation strategy based on active contour model and shape priori information, which can accurately and efficiently segment various images. The data fitting term, inspired by Chan-Vese (C-V) model, is used to guide the curve evolving to desired target boundary. Meanwhile, the contour is utilized to reconstruct a prior shape so that can help to deal with images in the presence of complex target. After that, the length regularity term of energy functional is incorporated to ensure the stable calculation of the evolution curve. The quantitative and qualitative experiments on various real and medical images indicate that our method is more efficient and accurate than the existing unified models.
Highlights
Segmentation of medical images can provide doctors with a variety of valuable information, so it plays an important role in many medical applications, such as treatment planning, surgery and prognosis assessment
To solve the problem of the C-V model, Li et al presented the region scalable fitting (RSF) model [7] based on the local information of the image, which has achieved promising results
PROPOSED METHOD we present an active contour model for various real and medical images segmentation
Summary
Segmentation of medical images can provide doctors with a variety of valuable information, so it plays an important role in many medical applications, such as treatment planning, surgery and prognosis assessment. To solve the problem of the C-V model, Li et al presented the region scalable fitting (RSF) model [7] based on the local information of the image, which has achieved promising results. In [8], Yang et al integrated the local information term and the distance constraint into the variational framework for auroral oval segmentation, it can achieve a significantly improvement and obtain more accurate boundaries. Based on the gravitational search technology, Çataloluk et al [10] implemented an improved C-V model to solve the local minimum problem. In [12], saliency map and color intensity are taken into the active contour model as the region external energy to identify a more accurate boundary positioning
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