Research

Publications | Communications | Manuscripts

Domain of expertise:

  • Computer-assisted surgery
  • Geometric constraints solving
  • Multi-objective optimization
  • Physically-based simulation
  • Medical simulators

Publications

 

Evolutionary approaches for surgical path planning: a quantitative study on Deep Brain Stimulation.

Noura Hamzé, Pierre Collet, and Caroline Essert. Evolutionary approaches for surgical path planning: a quantitative study on Deep Brain Stimulation. The IEEE Congress on Evolutionary Computation 2017, San Sebastian, Spain.

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 for the tool. After a previous clinical study in which we pointed out the interest of introducing MOEAs to neurosurgery. In this work, we aim at maximizing the range of optimal solutions proposed to the surgeon. Our study compares three different optimization approaches: an aggregative method using a weighted sum of the multiple constraints, an evolutionary multi-objective method, and an exhaustive dominance-based method used as ground truth. For each approach …

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Pareto front vs. weighted sum for automatic trajectory planning of Deep Brain Stimulation.

Noura Hamzé, 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.

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Introducing Pareto-based MOEA to Neurosurgery Preoperative path planning

Noura Hamzé, Pierre Collet, and Caroline Essert. Introducing Pareto-based MOEA to Neurosurgery Preoperative path planning, Genetic and Evolutionary Computation Conference (GECCO’16), 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 Parkinson’s 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.

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Pre-operative Trajectory Planning for Percutaneous Procedures in Deformable Environments

Noura Hamzé, Igor Peterlik, Stéphane 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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Anticipation of brain shift in Deep Brain Stimulation automatic planning

Noura Hamzé, Alexandre Bilger, Christian Duriez, Stéphane 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 (EMBC’15), 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.

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This paper is also available in a non-published version on 10 pages, you can download the full version here.

Communications

 

Poster MITK

Poster MITK: Presented with a Demo at the German Cancer Research Center DKFZ at the in MITK user’s 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 it’s my pleasure to be among.

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Poster Doctoral school

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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Manuscripts

 

Perspective geometry textures

Noura Hamzé, 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. Rémi Allègre

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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