Despite the advantages that 3D medical image analysis methods offer
and the fast introduction of CT and MRI, to date most hospitals use
radiographs to perform preoperative planning of hip surgeries and
automatic analysis of hip radiographs is still of interest. In this
paper, we present a novel method for segmentation of bone structures
in anterior-posterior (AP) radiographs based on Active Appearance
Models. The pelvis shape is decomposed in circular regions which
reflect convex local arrangement of shape points. A priori global
knowledge of the geometric structure of this region representation is
captured by a statistical deformable template integrating a set of
admissible deformations. The texture of each region is modeled
separately, and we build a local Active Appearance Model for each
region. A leave-one-out test was used to evaluate the performance of
the proposed method and to compare it with conventional Active
Appearance Model. The results demonstrate that the method is precise
and very robust to large-scale noise present in radiographs, and that
it can be useful in the context of preoperative planning of hip
surgery.
Many difficulties of color image processing may be resolved using specific color spaces. The problematic when discussing about image database is the same: in which color space a method will be the most effective. We present classical color spaces, and a tool able to represent images in these spaces in order to analyze which color space is the most relevant on the studied images. Secondly we will introduce hybrid color spaces. The basic idea of hybrid color spaces is to combine several color components from different color spaces in order to increase the effectiveness of color components to discriminate color data, and to reduce correlation rate between color components. Generally computed from an unique image we propose an extension of hybrid computation to generate Hybrid color space from image database. The main idea is to use a set of images as a unique image, and to realize statistical computation on this “virtual” image. Finally, we will present a system able to manage hybrid color space generation on images set, using Icobra and ColorSpace tools.
In this article, we present a new graphical navigation environment for image databases. Unlike "query by example" which focuses on similarities between images, the method we propose shows up visual differences occurring along paths offered to the user. Images are arranged to show an evolution along a direction, e.g. an axis that crosses the parameter space. This gives a global view of the database and allows the user to run all over the database in an organized way, and to focus on narrow areas by displaying sets of images.
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