Similarity measure is an important key in image registration. Most traditional intensity‐based
similarity measures (eg sum‐of‐squared‐differences, correlation coefficient, mutual …

Similarity measure is an important block in image registration. Most traditional intensity-
based similarity measures (eg, sum-of-squared-difference, correlation coefficient, and …

Similarity measure is an important part of image registration. The main challenge of similarity
measure is lack of robustness to different distortions. A well-known distortion is spatially …

This paper present an automatic 3D liver segmentation based on Active Shape Model. It
allows us to introduce a 3D modeling feature for the target organ to lead the segmentation …

The registration of images is a fundamental task in numerous applications in medical image
processing. Similarity measure is an important key in intensity based image registration …

Similarity measure is an important key in image registration. Most traditional intensity-based
similarity measures (eg, SSD, CC, MI, and CR) assume stationary image and pixel by pixel …

To avoid biopsies, doctors use non invasive medical techniques such as the computed
tomography. Even that, the detection of the liver remains a big challenge because of the …

Spatially-varying intensity noise is a common source of distortion in medical images and is
often associated with reduced accuracy in medical image registration. In this paper, we …

The problem addressed in this paper is matching corresponding regions in two images,
even when the image has correspondence deficiency and local deformations. We present a …