Computer systems play an important role in medical imaging industry since radiologists depend on it for visualization,
interpretation, communication and archiving. In particular, computer-aided diagnosis (CAD) systems help in lesion
detection tasks. This paper presents the design and the development of an interactive segmentation tool for breast cancer
screening and diagnosis. The tool conception is based upon a user-centered approach in order to ensure that the
application is of real benefit to radiologists. The analysis of user expectations, workflow and decision-making practices
give rise to the need for an interactive reporting system based on the BIRADS, that would not only include the numerical
features extracted from the segmentation of the findings in a structured manner, but also support human relevance
feedback as well. This way, the numerical results from segmentation can be either validated by end-users or enhanced
thanks to domain-experts subjective interpretation. Such a domain-expert centered system requires the segmentation to
be sufficiently accurate and locally adapted, and the features to be carefully selected in order to best suit user's
knowledge and to be of use in enhancing segmentation. Improving segmentation accuracy with relevance feedback and
providing radiologists with a user-friendly interface to support image analysis are the contributions of this work. The
preliminary result is first the tool conception, and second the improvement of the segmentation precision.
Reproducing a natural and real scene as we see in the real world everyday is becoming more and more popular.
Stereoscopic and multi-view techniques are used for this end. However due to the fact that more information are
displayed requires supporting technologies such as digital compression to ensure the storage and transmission
of the sequences. In this paper, a new scheme for stereo image coding is proposed. The original left and right
images are jointly coded. The main idea is to optimally exploit the existing correlation between the two images.
This is done by the design of an efficient transform that reduces the existing redundancy in the stereo image
pair. This approach was inspired by Lifting Scheme (LS). The novelty in our work is that the prediction step is
been replaced by an hybrid step that consists in disparity compensation followed by luminance correction and
an optimized prediction step. The proposed scheme can be used for lossless and for lossy coding. Experimental
results show improvement in terms of performance and complexity compared to recently proposed methods.
Medical information is evolving towards more complex multimedia data representation, as new imaging modalities
are made available by sophisticated devices. Features such as segmented lesions can now be extracted through
analysis techniques and need to be integrated into clinical patient data. The management of structured information
extracted from multimedia has been addressed in knowledge based annotation systems providing methods
to attach interpretative semantics to multimedia content. Building on these methods, we develop a new clinical
imaging annotation system for computer aided breast cancer screening. The proposed system aims at more
consistent, efficient and standardised data mark-up of digital and digitalised radiology images. The objective is
to provide detailed characterisation of abnormalities as an aid in the diagnostic task through integrated annotation
management. The system combines imaging analysis results and radiologist diagnostic information about
suspicious findings by mapping well-established visual and low-level descriptors into pathology specific profiles.
The versatile characterisation allows differentiating annotation descriptors for different types of findings. Our
approach of semi-automatic integrated annotations supports increased quality assurance in screening practice.
This is achieved through detailed and objective patient imaging information while providing user-friendly means
for their manipulation that is oriented to relieving the radiologist's workload.
This paper introduces a new construction of quincunx wavelet transform. This new transform is a bidimensional extension of the factorization of wavelet transform into lifting scheme for finite and symmetrical low pass filters. The aim of this method is to deal with quincunx images by appropriate transforms while using advantages offered by the lifting scheme. Indeed, quincunx sampling is of big interest for image coding applications. For example recent remote sensors of satellites return quincunx sampled images. Moreover, a quincunx sampling allows the decomposition of the image into two channels and to have a twice as accurate multiresolution analysis as the dyadic one.