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(classic 3D imaging but also 2D "temporal"
corresponding to a double synchronisation on
respiration and heartbeat), (ii). evaluation of a
local correction approach and (iii). Improvement
of the signal to noise ratio and of the resolution of
individual images synchronised at various
instants of the respiratory cycle (application of a
super-resolution algorithm).
Multi-resolution approach in multi-modality
imaging
The advantages of this approach compared to the
previous ones are multiple. The most important
are avoiding the segmentation stages of the
concerned structures in the two images before
applying correction, and generating whole
corrected images (not simply corrected values
for concerned regions). However, in this
approach the liaison model between the lowresolution
details of the image and the
anatomical image is global, the average is
calculated for the whole image and is applied
throughout. This global approach is likely to
introduce artefacts into the emission images
when there is not a good correspondence
between the functional and the anatomical data.
Two approaches have been developed to resolve
these limitations. The first is based on the use of
a local model and the second on the development
of algorithms which use no anatomical
information
Segmentation of functional volumes
Mathieu Hatt defended his PhD thesis. A patent
was taken out in September 2008 for an
algorithm developed during his thesis. To
validate the universal aspect and the robustness
of the proposed methodology a database of
images acquired from different hospitals and
different machines was used. The clinical impact
of this approach will be evaluated in the ANR
(Emergence TEC) “SIFR” project.
Integration of PET/scan imagery in radiotherapy
We began our activity in this domain with a
generic model of respiratory movement. From
TDM 4D data and using a technique of
deformable registration we propose a method
allowing to construct an initial spatio-temporal
model of the breathing thorax, for each patient.
Such a model could remain simple, taking into
consideration only one respiratory cycle. We
added a first improvement, which consisted of
globally modelling the trajectories in function of
the amplitude of the external respiratory signal.
This first approach allowed to obtain continuous
spatio-temporal data following an irregular
respiratory cycle. Secondly it would be
interesting to add a parameter representing the
non-regularity of the cycle, which would allow to
define a more generic model controlled by a
series of temporal signals obtained during the
session in the treatment room. To do this we
could, for example, use a spirometer, giving
respiratory volume, an image of the surface of
the thorax coming from optic sensors, X-ray
images or new systems of detection TOF which
we are currently evaluating. It means going
towards a multi-dimensional model allowing to
analyse a posteriori the temporal conditions of
irradiation.
2. Theme 2
Team Indexation, tracability and integrity
of multi-media information
Work developed in this theme essentially
concerns generating and handling traces of
medical information for indexing and content
search, especially in image databases (Content
Based Image Retrieval), in order to help with
diagnosis and decision making, and also to
ensure the security of information and guarantee
the reliability of transmitted data.
Work in CBIR has evolved since 2007 towards
search of entire patient records, containing both
images and text documents (medical records and
administrative papers). It led in 2008 to the
development of new methods, in automatic
digital image characterisation [15], and adapting
data search methods to CBFR (Content Based
File Retrieval) [21] and knowledge extraction
[22][3]. The methods used gave results of 82%
(Brest University Hospital diabetics retinopathies
database) to 92% (DDSM-Massachusetts General
Hospital database) in terms of retrieval efficacy.
Concerning security, work was essentially in
medical imaging data, although it is now moving
towards more global studies, into image
databases. The aim is to supply innovative
solutions to ensure feasibility and traceability of
data at the interface of data and information
systems [12]. Initial work focuses on the integrity