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Domain
of expertise: - Computer-aided planning for
minimally-invasive surgery - Geometric constraints solving - Multi-objective optimization - Biomechanical simulation |
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Noura Hamzˇ, Jimmy Voirin, Pierre Collet,
Pierre Jannin, Claire Haegelen, and Caroline Essert. Pareto front vs. weighted sum for automatic
trajectory planning of Deep Brain Stimulation. The 19th International
Conference on Medical Image Computing and Computer Assisted Intervention
(MICCAI), Athens, Greece, October 2016.
Conference paper Abstract : Preoperative path planning for Deep Brain
Stimulation(DBS) is a multi-objective optimization problem consisting in
searching the best compromise between multiple placement constraints. Its
automation is usually addressed by turning the problem into mono-objective
thanks to an aggregative approach. However, despite its intuitiveness, this
approach is known for its incapacity to find all optimal solutions. In this
work, we introduce an approach based on multi-objective dominance to DBS path
planning. We compare it to a classical aggregative weighted sum of the
multiple constraints and to a manual planning thanks to a retrospective study
performed by a neurosurgeon on 14 DBS cases. The results show that the
dominance-based method is preferred over manual planning, and covers a larger
choice of relevant optimal entry points than the traditional weighted sum
approach which discards interesting solutions that could be preferred by
surgeons. To appear |
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Noura Hamzˇ, Pierre Collet, and Caroline
Essert. Introducing
Pareto-based MOEA to Neurosurgery Preoperative path planning, Genetic
and Evolutionary Computation Conference (GECCOÕ16), Denver, United States,
July 2016. Short paper / poster. doi: 10.1145/2908961.2909028 Conference paper Abstract : This paper presents the first implementation
of NSGA-II in neurosurgery preoperative path planning. Deep Brain Stimulation
(DBS) is a surgical treatment of ParkinsonÕs dis- ease that can be regarded as
a multi-objective optimization problem, searching for the best compromise
between multiple electrode placement rules. Most of the current automatic
decision-making processes use aggregative approaches with single objective
optimization, even though they are known for their inability to find all
Pareto-optimal solutions. Firstly, we show this is the case on 20 datasets of
patients by comparing our implementation of NSGA-II to the weighted sum (WS)
strategy. Then, we show it requires about 9 hours to find equivalent results
using a deterministic scan of the search space where NSGA-II does it in about
3mn. This paper presents an objective validation that even simple techniques
such as NSGA-II should be used by surgeons over more intuitive weighted based
methods. This paper is also available in a non-published version on 8 pages, you
can download the full version here. |
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Noura Hamzˇ, Igor Peterlik, Stˇphane Cotin,
and Caroline Essert. Pre-operative
Trajectory Planning for Percutaneous Procedures in Deformable Environments,
Computerized Medical Imaging and Graphics, Elsevier, page 16-28, Volume 47,
January 2016. doi:10.1016/j.compmedimag.2015.10.002 Journal paper Abstract : In image-guided percutaneous interventions, a
precise planning of the needle path is a key factor to a successful
intervention. In this paper we propose a novel method for computing a
patient-specific optimal path for such interventions, accounting for both the
deformation of the needle and soft tissues due to the insertion of the needle
in the body. To achieve this objective, we propose an optimization method for
estimating preoperatively a curved trajectory allowing to
reach a target even in the case of tissue motion and needle bending.
Needle insertions are simulated and regarded as evaluations of the objective
function by the iterative planning process. In order to test the planning
algorithm, it is coupled with a fast needle insertion simulation involving a
flexible needle model and soft tissue finite element modeling, and
experimented on the use-case of thermal ablation of liver tumors. Our
algorithm has been successfully tested on twelve datasets of patient-specific
geometries. Fast convergence to the actual optimal solution has been shown.
This method is designed to be adapted to a wide range of percutaneous
interventions. |
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Noura Hamzˇ, Alexandre Bilger, Christian
Duriez, Stˇphane Cotin, and Caroline Essert. Anticipation of brain shift in Deep Brain Stimulation
automatic planning, 37th Annual International Conference of the IEEE
Engineering in Medicine and Biology Society (EMBCÕ15), Milano, Italy, pages
3635 - 3638, August 2015. doi:10.1109/EMBC.2015.7319180
Conference paper Abstract : Deep Brain Stimulation is a neurosurgery
procedure consisting in implanting an electrode in a deep structure of the
brain. This intervention requires a preoperative planning phase, with a
millimetric accuracy, in which surgeons decide the best placement of the
electrode depending on a set of surgical rules. However, brain tissues may
deform during the surgery because of the brain shift phenomenon, leading the
electrode to mistake the target, or moreover to damage a vital anatomical
structure. In this paper, we present a patient-specific automatic planning
approach for DBS procedures which accounts for brain deformation. Our
approach couples an optimization algorithm with FEM based brain shift
simulation. The system was tested successfully on a patient-specific 3D
model, and was compared to a planning without considering brain shift. The
obtained results point out the importance of performing planning in dynamic
conditions. This paper is
also available in a non-published version on 10 pages, you can download the
full version here. |
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Poster
MITK: Presented with a Demo at the German Cancer Research Center DKFZ at the in MITK userÕs meeting 2015.
The event took place in Heidelberg, Germany. MITK
is a Medical
Imaging Interaction Toolkit elaborated by DKFZ research group. You may think
about it as the german alternative of 3D Slicer . Yes it is !
and it has many adepts worldwide, and itÕs my plesure to be among. |
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Poster
Doctoral school: Presented
at the doctoral school of mathematics
and informatics follow up day after the first year of the thesis. The
event took place in Strasbourg, France. |
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Non-published Papers |
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Noura Hamzˇ, Pierre Collet, and Caroline
Essert. Trajectory
planning for minimally invasive surgery: Is the weighted sum approach really
sufficient? The 7th International Conference on Information Processing
in Computer-Assisted Interventions (IPCAI). June2016, Heidelberg, Germany. Abstract
: Path planning for
surgical tools in minimally invasive surgery is a multi-objective
optimization problem consisting in searching the best compromise between
multiple placement constraints to find an optimal insertion point. Many works
have been proposed to automatize the decision- making process. Most of them
use an aggregative approach that transforms the problem into a mono-objective
problem. However, despite its intuitive-ness, this approach is known for its
incapacity to find all optimal solutions. In this work, we confront different
approaches to maximize the range of optimal solutions. This work requires clinical validation to point
out its feasibility. |
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Noura Hamzˇ, Perspective geometry textures. Computer science
and image science master, second year, six month
internship report, IGG research group, ICube
laboratory, University of Strasbourg. Supervised by Dr. Rˇmi All¸gre Abstract : In this work, we study the problem of
decomposing a 3D surface into a compact set of height maps that offers
optimal rendering performance. Based on this study, we propose a new approach
to decompose the surface of a solid 3D model represented as a triangle mesh
into a set of height maps defined with a perspective projection. Our method
can be considered as an improvement and an extension of the Geometry Textures
representation. We show that our decomposition technique achieves better
storage compactness than previous height maps decomposition techniques. |
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Last updated on August 2016 |
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