دورية أكاديمية
Unsupervised active contours driven by density distance and local fitting energy with applications to medical image segmentation.
العنوان: | Unsupervised active contours driven by density distance and local fitting energy with applications to medical image segmentation. |
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المؤلفون: | Shyu, Kuo-Kai, Pham, Van-Truong, Tran, Thi-Thao, Lee, Po-Lei |
المصدر: | Machine Vision & Applications; Nov2012, Vol. 23 Issue 6, p1159-1175, 17p, 9 Color Photographs, 2 Graphs |
مصطلحات موضوعية: | MEDICAL imaging systems, IMAGE segmentation, THREE-dimensional imaging, PROBABILITY theory, MAGNETIC resonance imaging, TOMOGRAPHY |
مستخلص: | This study presents an efficient variational region-based active contour model for segmenting images without priori knowledge about the object or background. In order to handle intensity inhomogeneities and noise, we propose to integrate into the region-based local intensity model a global density distance inspired by the Bhattacharyya flow. The local term based on local information of segmented image allows the model to deal with bias field artifact, which arises in data acquisition processes. The global term, which is based on the density distance between the probability distribution functions of image intensity inside and outside the active contour, provides information for accurate segmentation, keeps the curve from spilling, and addresses noise in the image. Intensive 2D and 3D experiments on many imaging modalities of medical fields such as computed tomography, magnetic resonance imaging, and ultrasound images demonstrate the effectiveness of the model when dealing with images with blurred object boundary, intensity inhomogeneities, and noise. [ABSTRACT FROM AUTHOR] |
Copyright of Machine Vision & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
قاعدة البيانات: | Complementary Index |
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