From WWWwikiEn<span style="display: none;">[[Image:Fusion11_Bogatyrenko]][[Image:ACC11_Bogatyrenko]][[Image:IROS10_BogatyrenkoNoack]][[Image:IJCARS10_Bogatyrenko.pdf]][[Image:MFI10_Bogatyrenko.pdf]][[Image:IROS09_Bogatyrenko.pdf]]</span> <span style="display: none;">[[Image:Fusion11_Bogatyrenko]][[Image:ACC11_Bogatyrenko]][[Image:IROS10_BogatyrenkoNoack]][[Image:IJCARS10_Bogatyrenko.pdf]][[Image:MFI10_Bogatyrenko.pdf]][[Image:IROS09_Bogatyrenko.pdf]]</span>

Evgeniya Ballmann

	MSc Research Assistant, Ph.D. Student
	Address:	Karlsruher Institut für Technologie Institut für Anthropomatik Gebäude 50.20 Raum 129 Adenauerring 2 D-76131 Karlsruhe
	Walk-in hours:	on arrangement
	Phone:	+49-721-608-44354
	E-mail:	Evgeniya.Ballmann@kit.edu

Academic Career

Research Interests

• Biomedical engineering
• State and parameter estimation of distributed physical systems
• Computational mechanics
• Computer vison

DFG Research Training Group 1126 "Intelligent surgery - development of new computer-based methods for the future working environment in visceral surgery"

Teaching

• Tutor and coordinator of the laboratory Praktikum: Forschungsprojekt "Intelligente Sensor-Aktor-Systeme" (winter term 2008/2009 to summer term 2010)

Publications

Proceedings of the 14th International Conference on Information Fusion (Fusion 2011), Chicago, Illinois, USA, July, 2011.

Author : Evgeniya Bogatyrenko, Uwe D. Hanebeck
Title : Adaptive Model-Based Visual Stabilization of Image Sequences
In : Proceedings of the 14th International Conference on Information Fusion (Fusion 2011)
Date : July 2011

Abstract

Visual stabilization proposed in this paper compensates changes of the scene caused by motion and deformation of an observed object.
This is of high importance in computer-assisted beating heart surgery, where the views of the beating heart should be stabilized.
The proposed model-based method defines visual stabilization as a transformation of the current image sequence to a stabilized image sequence.
This transformation incorporates physical model of the observed object and model of the measurement process.
In contrast to standard approaches, the quality of the visual stabilization is continuously evaluated and improved in two aspects. On the one hand,
discretization errors are reduced. On the other hand, the parameters of the underlying models are adjusted.
The performance of the proposed method is evaluated in an experiment with a pressure-regulated artificial heart.
Compared with standard methods, the model-based method provides higher accuracy, which is additionally improved by a feedback mechanism.

Proceedings of the 2011 American Control Conference (ACC 2011), San Francisco, California, USA, June, 2011.

Author : Evgeniya Bogatyrenko, Uwe D. Hanebeck
Title : Visual Stabilization of a Beating Heart Motion by Model-Based Transformation of Image Sequences
In : Proceedings of the 2011 American Control Conference (ACC 2011)
Date : June 2011

Abstract

In order to assist a surgeon by operating on a beating heart, visual stabilization makes the beating heart appear still to a surgeon
by providing the current heart view as stationary and non-moving. In this way, the surgeon is not disturbed during an operation by a motion of the heart
and can get an impression of performing conventional surgery.
In contrast to existing methods for visual stabilization, the proposed approach involves a model-based transformation of image sequences provided by a camera system.
This transformation incorporates the knowledge of physical characteristics of the heart in form of a mathematical model of the heart surface.
Its main advantage is that the uncertainties of the model and measurements are considered. This occurs by estimating the parameters of the transformation.
Furthermore, the quality of the visual stabilization is additionally improved by adapting the parameters of the underlying physical model.
A performance of the proposed approach is evaluated in an experiment with a pressure-regulated artificial heart. In comparison to standard approaches,
it provides superior results illustrating the high quality of the visual stabilization.

Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), Taipei, Taiwan, October, 2010.

Author : Evgeniya Bogatyrenko, Benjamin Noack, Uwe D. Hanebeck
Title : Reliable Estimation of Heart Surface Motion under Stochastic and Unknown but Bounded Systematic Uncertainties
In : Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010)
Date : October 2010

Abstract

A reliable estimation of heart surface motion
is an important prerequisite for the synchronization of surgical
instruments in robotic beating heart surgery. In general, only
an imprecise description of the heart dynamics and measurement
systems is available. This means that the estimation of heart
motion is corrupted by stochastic and systematic uncertainties.
Without consideration of these uncertainties, the obtained results
will be inaccurate and a safe robotic operation cannot be guaranteed.
Until now, existing approaches for estimating the motion of the
heart surface are either deterministic or treat only stochastic
uncertainties. The proposed method extends the heart motion
estimation to the simultaneous consideration of stochastic and
unknown but bounded systematic uncertainties. It computes dynamic
bounds in order to provide the surgeon with a guidance by
constraining the motion of the surgical instruments and thereby
protecting sensitive tissue.

International Journal of Computer Assisted Radiology and Surgery (IJCARS 2010), 6(3):387-399, August, 2010.

URL

Author : Evgeniya Bogatyrenko, Pascal Pompey, Uwe D. Hanebeck
Title : Efficient Physics-Based Tracking of Heart Surface Motion for Beating Heart Surgery Robotic Systems
In : International Journal of Computer Assisted Radiology and Surgery (IJCARS 2010)
Date : August 2010

Abstract

Purpose: Tracking of beating heart motion in a robotic
surgery system is required for complex cardiovascular interventions.
Methods: A heart surface motion tracking method is developed,
including a stochastic physics-based heart surface
model and an efficient reconstruction algorithm. The algorithm
uses the constraints provided by the model that exploits
the physical characteristics of the heart. The main advantage
of the model is that it is more realistic than most standard
heartmodels. Additionally, no explicit matching between the
measurements and the model is required. The application of
meshless methods significantly reduces the complexity of
physics-based tracking.
Results: Based on the stochastic physical model of the heart
surface, this approach considers the motion of the intervention
area and is robust to occlusions and reflections. The
tracking algorithm is evaluated in simulations and experiments
on an artificial heart. Providing higher accuracy than
the standardmodel-based methods, it successfully copes with
occlusions and provides high performance even when all
measurements are not available.
Conclusions: Combining the physical and stochastic description
of the heart surface motion ensures physically correct
and accurate prediction. Automatic initialization of the physics-based
cardiac motion tracking enables system evaluation
in a clinical environment.

Proceedings of the 2010 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2010), Salt Lake City, Utah, USA, September, 2010.

Author : Evgeniya Bogatyrenko, Uwe D. Hanebeck
Title : Simultaneous State and Parameter Estimation for Physics-Based Tracking of Heart Surface Motion
In : Proceedings of the 2010 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2010)
Date : September 2010

Abstract

Most existing approaches for tracking of the
beating heart motion assume known cardiac kinematics and
material parameters. However, these assumptions are not realistic
for application in beating heart surgery. In this paper,
a novel probabilistic tracking approach based on a physical
model of the heart surface is presented. In contrast to existing
approaches, the physical information about heart kinematics
and material properties is incorporated and considered in
an estimation of the heart behavior. An additional advantage
is that the time-dependencies and uncertainties of the heart
parameters are efficiently handled by exploiting simultaneous
state and parameter estimation. Furthermore, by decomposing
the state into linear and nonlinear substructures, the computational
complexity of the estimation problem is reduced. The
experimental results demonstrate the high performance of the
method proposed in this paper. The solution of the parameter
identification problem allows a personalized physical model and
opens up possibilities to apply the physics-based tracking of the
heart surface motion in a clinical environment.

Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009), October, 2009.

Author : Evgeniya Bogatyrenko, Uwe D. Hanebeck, Gabor Szabo
Title : Heart Surface Motion Estimation Framework for Robotic Surgery Employing Meshless Methods
In : Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009)
Date : October 2009

Abstract

A novel heart surface motion estimation frame-
work for a robotic surgery on a stabilized beating heart is
proposed. It includes an approach for the reconstruction and
prediction of heart surface motion based on a novel physical
model of the intervention area described by a distributed-
parameter system. Instead of conventional element methods, a
meshless method is used for a spatial and temporal decomposi-
tion of this system. This leads to a finite-dimensional state-space
form. Furthermore, the state of the resulting lumped-parameter
system, which provides an approximation of the deflection and
velocity of the heart surface, is dynamically estimated under
consideration of uncertainties both occurring in the system
and arising from noisy camera measurements. By using the
estimation results, an accurate reconstruction of heart surface
motion for the synchronisation of the surgical instruments is
also achieved at occluded or non-measurement points.

Selected Talks

2011

Evgeniya Bogatyrenko, Uwe D. Hanebeck
Adaptive Model-Based Visual Stabilization of Image Sequences
14th International Conference on Information Fusion (Fusion 2011), Chicago, Illinois, USA, July, 2011.

Evgeniya Bogatyrenko, Uwe D. Hanebeck
Visual Stabilization of a Beating Heart Motion by Model-Based Transformation of Image Sequences
American Control Conference (ACC 2011), San Francisco, California, USA, June, 2011.

2010

Evgeniya Bogatyrenko, Benjamin Noack, Uwe D. Hanebeck
Reliable Estimation of Heart Surface Motion under Stochastic and Unknown but Bounded Systematic Uncertainties
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), Taipei, Taiwan, October, 2010.

Evgeniya Bogatyrenko, Uwe D. Hanebeck
Simultaneous State and Parameter Estimation for Physics-Based Tracking of Heart Surface Motion
IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2010), Salt Lake City, Utah, USA, September, 2010.

2009

Evgeniya Bogatyrenko, Gabor Szabo, Uwe D. Hanebeck
Heart Surface Motion Estimation Framework for Robotic Surgery Employing Meshless Methods
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009), St. Louis, MO, USA, October, 2009

Evgeniya Bogatyrenko
Framework for Model-based Estimation of Heart Motion
Meeting of the professional group Visual Computing in Medicine
German Cancer Research Center, Heidelberg, March 25, 2009