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	    2016</a> | <a href="http://www.inria.fr/en/teams/asclepios">Presentation of the Project-Team ASCLEPIOS</a> | <a href="http://team.inria.fr/asclepios/">ASCLEPIOS Web Site
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        <h2>Section: 
      Research Program</h2>
        <h3 class="titre3">Computational Physiology</h3>
        <p>The objective of Computational Physiology (CP) is to provide
models of the major functions of the human body and numerical
methods to simulate them. The main applications are in medicine
where CP can for instance be used to better
understand the basic processes leading to the appearance of a
pathology, to model its probable evolution and to plan, simulate,
and monitor its therapy.</p>
        <p>Quite advanced models have already been proposed to study at the
molecular, cellular and organ level a number of physiological
systems (see for instance
<a href="./bibliography.html#asclepios-2016-bid21">[81]</a>, <a href="./bibliography.html#asclepios-2016-bid22">[78]</a>, <a href="./bibliography.html#asclepios-2016-bid23">[69]</a>, <a href="./bibliography.html#asclepios-2016-bid24">[82]</a>, <a href="./bibliography.html#asclepios-2016-bid25">[75]</a>).
While these models and new ones need to be developed, refined or
validated, a grand challenge that we want to address in this
project is the automatic adaptation of the model to a given
patient by comparing the model with the available biomedical
images and signals and possibly also some additional
information (e.g. genetic). Building such <i>patient-specific
models</i> is an ambitious goal, which requires the choice or
construction of models with a complexity adapted to the resolution
of the accessible measurements and the development of
new data assimilation methods coping with massive numbers of
measurements and unknowns.</p>
        <p>There is a hierarchy of modeling levels for CP models of the human body
<a href="./bibliography.html#asclepios-2016-bid26">[70]</a>:</p>
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          <li>
            <p class="notaparagraph"><a name="uid24"> </a>the first level is mainly geometrical, and addresses the
construction of a digital description of the anatomy
<a href="./bibliography.html#asclepios-2016-bid27">[65]</a>, essentially acquired from medical
imagery;</p>
          </li>
          <li>
            <p class="notaparagraph"><a name="uid25"> </a>the second level is physical, involving mainly the
biomechanical modeling of various tissues, organs, vessels,
muscles and bone structures  <a href="./bibliography.html#asclepios-2016-bid28">[76]</a>;</p>
          </li>
          <li>
            <p class="notaparagraph"><a name="uid26"> </a>the third level is physiological, involving the modeling of
the functions of the major organ systems  <a href="./bibliography.html#asclepios-2016-bid29">[77]</a>
(e.g. cardiovascular, respiratory, digestive, central or
peripheral nervous, muscular, reproductive, hormonal) or some
pathological metabolism (e.g. evolution of cancerous or
inflammatory lesions, formation of vessel stenoses, etc.); and</p>
          </li>
          <li>
            <p class="notaparagraph"><a name="uid27"> </a>a fourth level is cognitive, modeling the higher functions of
the human brain <a href="./bibliography.html#asclepios-2016-bid30">[56]</a>.</p>
          </li>
        </ul>
        <p>These different levels of modeling are closely related to each other,
and several physiological systems may interact with each other (e.g. the
cardiopulmonary interaction <a href="./bibliography.html#asclepios-2016-bid31">[79]</a>). The choice
of the resolution at which each level is described is important, and
may vary from microscopic to macroscopic, ideally through multiscale
descriptions.</p>
        <p>Building this complete hierarchy of models is necessary to evolve from
a <i>Visible Human project</i> (essentially the first level of modeling)
to a much more ambitious <i>Physiological Human project</i> (see
<a href="./bibliography.html#asclepios-2016-bid29">[77]</a>, <a href="./bibliography.html#asclepios-2016-bid22">[78]</a>). We will not address all the issues
raised by this ambitious project, but instead focus on the topics detailed
below. Among them, our objective is to identify some common methods
for the resolution of the large inverse problem raised by the
coupling of physiological models and medical images for the
construction of patient-specific models (e.g. specific variational or
sequential methods (EKF), dedicated particle filters). We also
plan to develop specific expertise in the extraction of geometrical
meshes from medical images for their further use in simulation
procedures. Finally, computational models can be used for specific
image analysis problems studied in
section <a title="Medical Image Analysis" href="./uid9.html">3.2</a> (e.g. segmentation,
registration, tracking). Application domains include</p>
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            <p class="notaparagraph"><a name="uid28"> </a>surgery simulation;</p>
          </li>
          <li>
            <p class="notaparagraph"><a name="uid29"> </a>cardiac Imaging;</p>
          </li>
          <li>
            <p class="notaparagraph"><a name="uid30"> </a>brain tumors, neo-angiogenesis, wound healing processes,
ovocyte regulation, etc.</p>
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