Image processing and visualization topics Image processing and visualization topics

Cardiovascular medical imaging, in particular echocardiography and cardiac magnetic resonance imaging, has reached a level that provides significant added value for cardiologists in diagnosing cardiovascular diseases.At present most clinical tools are modality specific and relevant information is merged retrospectively by the cardiologist.Assuming that combining multi-modal anatomical and functional information allows for a quicker assessment of a given case, the goal is to provide improved diagnostic tools that enhance both the qualitative (e.g. data visualization and fusion) and quantitative (e.g. more accurate functional measures based on several data sources) assessment process.This would benefit the quantification process in the daily clinic and would enable the creation of improved anatomic and functional cardiac models that enable the physiological understanding of the heart in healthy and diseased cases.The proposed projects are suitable for project/master work.1. Augmented reality for live ultrasound scanningCurrently the successful employment of ultrasound is highly dependent on the experience of the examiner. During acquisition, in addition to the cognitive load associated with interpreting the image, the examiner has to control the correct positioning and orientation of the transducer in order to ensure that the correct anatomical area is imaged and that the image quality is satisfactory.By providing visual guidance through overlays, which communicate the anatomical structures being imaged, one can greatly improve the understanding of the structural arrangement of tissues during the scanning procedure. Thus it is highly desirable to assist the ultrasound examiner and as such partially alleviate the burden of image interpretation.The aim of the project is to develop 2D/3D visualization methods that enable the clinician to find a visual correspondence between the ultrasound data being acquired and a generic anatomical mesh-model of a human heart.

Figure: Standard ultrasound slice augmented with anatomical information from a highly descriptive cardiac mesh model.Objectives: Real-time generation of augmented views on the tablet, investigate the possibilities for generating advanced visualizations and implement them directly on the tablet. Non-rigid mesh deformation of the heart model based on existing anatomic landmarks Testing of the system during live scanningSkills: Knowledge of C++ programming Desire to learn Open GLSL and Android programmingContact: Gabriel Kiss or Hans Torp2. Real-time fusion of multi-modal cardiac data on the GPUFull 3D datasets of the heart can be acquired using different imaging modalities e.g. 3D echocardiography (3D echo) and cardiac magnetic resonance imaging (CMR).Using image fusion the strengths of different image modalities can be combined. As such, by co-registering multi-modal datasets, a direct spatial relationship between anatomical and functional information in the underlying data is established and visualized.Furthermore in the case of 3D echo the image quality has large variations between subjects, the spatial resolution varies with depth and the tissue contrast is angle dependent. One possibility of improving image to noise ratio and to extend the field of view is to acquire multiple datasets from different angles, detect corresponding features in each view and fuse the recordings in order to generate a combined volume.The aim of the project is to develop data registration techniques for fusing multiple 3D cardiac acquisitions with the goal of improving signal-to-noise ratio, spatial resolution and field of view (3D echo to 3D echo volumetric fusion) or to improve the diagnostic process (3D echo to CMR alignment) and to demonstrate their applicability during live scanning.

Figure: Top row: fusion of 3D echocardiographic and CMR data. Bottom row: registration of 3D echocardiographic data acquired from different views (e.g. parasternal, apical)Objectives: Extend and customize the current registration methods for multimodal 3D cardiac data Improve the registration method relying on data from an optical tracking system Validate the developed methods during live scanningSkills: Knowledge of C++ programming (existing code implemented in C++) Desire to learn parallel computing (CUDA or OpenCL)Contact: Gabriel Kiss or Hans TorpLink to this Back Ultrasound Mediated Drug Delivery

To minimize undesired side effects of cancer drugs on normal tissue, several groups are working on encapsulating the cancer drugs into particles of diameter ~ 100 nm. The delivery of both the particles and the drugs can be enhanced by ultrasound.The capillaries in a tumor grow aggressively with an imperfect wall, so that these particles leak into the space between tumor cells (the interstitium), while they are maintained in the blood stream in normal tissue, which has well developed capillary walls. Encapsulating the smaller anti-cancer drug molecules into particles opens for selective pharmacological treatment of tumor tissue, while normal tissue is not exposed to the drug.Ultrasound radiation force can increase transport of the particles deeper into the interstitium. Increase of temperature produced by ultrasound absorption will also increase diffusion of the particles into the interstitium.Ultrasound can also be used to break the particles. This seems to be stimulated by cavitation of small gas-bubble nuclei in the tissue. It is therefore a very interesting strategy to combine small gas bubbles (diam ~ 2m) and the drug encapsulating nano-particles with ultrasound.There are several interesting Master and PhD topics in this field, ranging from multi-frequency ultrasound acoustics and transducer arrays for imaging of particles and stimulated transport and breakage of the particles signal processing for multi-frequency ultrasound imaging (SURF Imaging) of the particles combined optical imaging of particles with ultrasound mediated drug delivery experimental studies of ultrasound mediated transport and breakage of gas micro-bubbles and drug encapsulating nano-particles in lab models and small animal tumor modelsContact: Professor Bjrn Angelsen Researcher Rune HansenLink to this Back Beamforming topics Beamforming topics

Ultrasound beamforming is about controlling the interference pattern of the acoustical waves emitted by several small piezo-electric elements at the tip of a transducer. If you apply an alternating voltage signal to an piezo-electric element, it will start vibrating and emit sound. If you select the spacing between your elements and the delay in the elements'signals just right, you can create an interference pattern that's to your benefit, in particular one in which the majority of the signal energy all goes out in one angular direction.When using the transducer to receive sound, the principles are the same. Received sound vibrations at the elements will be converted to an electric signal. Adjust the amplitude anddelays of the received signal on each element before summing, and you'll be able to receive from a chosen angular direction.1. New beamforming techniques based on spatial coherenceConventional ultrasound images are formed by delay-and-sum beamforming of the backscattered echoes received by the transducer elements. Such an interferential process can however be challenged in the presence of phase aberrations, acoustic reverberation clutters, strong off-axis targets or electronic noise. These phenomenons will all contribute in decreasing the spatial coherence of the received ultrasound signal across the aperture of the transducer, and will result in blurring artifacts in the delay-and-sum ultrasound image.Modern ultrasound scanners allow for software processing of the data received by all the transducer elements. We can now test new beamforming techniques that can cope better with in-vivo acoustic perturbations, resulting therefore in a better contrast and signal-to-noise ratio. Several beamforming techniques based on the coherence of the received data have been proposed lately, promising for better ultrasound images using a non-linear beamforming scheme.Aim: Implement and test new beamforming algorithms based on spatial coherence Apply them on simulated and in-vivo collected channel data, and compare with B-mode imagesQualifications: Interested in ultrasound medical imaging Signal processing Matlab programming skillsContact persons: Bastien Denarie Hans Torp2. Estimation and correction of speed of soundBackground:Ultrasound imaging of tissue always assumes a sound velocity of 1540 m/s. This is close to correct on average, but not always. In extreme cases, with a high percentage of fatty tissue, the actual average velocity can be as low as 1400 m/s. This causes the ultrasound image to completely collapse. Estimating and correcting the actual speed of sound in these cases can bring back the ultrasound image.Including such correction in modern ultrasound scanners will have a large clinical importance and will enable better/more accurate diagnosis on difficult patients.Our Ultrasound lab now has excellent availability of raw data for doing such estimation on in-vivo data.Aim: Investigate methods for automatic estimation of sound velocity. Test methods in simulations Test methods on in-vitro and in-vivo data.Qualifications: Medical ultrasound theory/acoustics Signal processing Mathematics Matlab programmingContact persons: Hans Torp Bastien Denarie Tore BjaastadExample of impact of speed of sound correction - from Phillips (pdf)3. Detection and compensation for blocked/noisy channelsBackground:The ultrasound scanners of today typically blindly utilize data from all probe elements without any form of analysis. In the future, raw channel data will be available for real time processing on a CPU inside a ultrasound machine. This allows analysis of the data prior to beamforming. A simple, yet potentially very usefull analysis, is to check whether an element is contributing positively to the beamformer sum. In some cases elements might be blocked. For example by ribs. Elements could also be broken, or electronics for a channel could be broken. In all these cases it would be beneficial to exclude data from these channels/elements.Our Ultrasound lab provides excellent availability of raw data for testing out the impact of such errors and the benefits of correcting for them.Aim: Investigate/develop techniques for detecting and compensating for blocked/broken channels. Test techniques in simulations Test techniques on in-vivo and in-vitro data.Qualifications: Signal processing Matlab programmingContactpersons: Hans Torp Bastien Denarie Tore BjaastadLink to this Back Doppler imaging of blood flow Doppler imaging of blood flow

Blood gives very weak echoes compared to the surrounding tissue, and it is usually not visible in ultrasound images. But since the blood is moving, it creates a Doppler-shift in the returning echoes. This makes it possible to filter out just the signal from moving blood and detect the velocity of the blood from the Doppler shift.Some established methods for presenting this information is Color Flow Doppler and Pulsed Wave Doppler, as shown in the figures on the right: PW Doppler (upper panel) and Color Flow (lower panel) are well established methods for imaging blood flow1: Simulation models for Doppler imaging based on computational fluid dynamics (patient specific models)There is increasing interest in using advanced computational models for flow based on computation fluid dynamics (CFD) as input to ultrasound imaging simulations. This gives the possibility to develop and compare new imaging algorithms towards a realistic ground truth where all information of scatterer movement is available. We have previously developed a framework for these simulations in cooperation with the University in Ghent, Belgium. However, the simulations can take a long time to finish (~days), and it is critical to find approaches to reduce this time during development. In this project you will work with the trade-off between simulation accuracy and time for producing realistic Doppler signals from both patient specific CFD-models and a more ideal jet-flow. In addition to the simulations, a new flow imaging algorithm will be investigated based on ultrafast acquisition scheme, providing an image frame rate > 1000 fps.Preferred qualifications: Programming in Matlab.Contact:Professor Hans Torp, Researcher Lasse Lvstakken2: Tracking of complex blood flow in congenital heart disease (babies)Cardiac flow patterns may reveal several kinds of cardiovascular disease. Well known examples include the detection and quantification of leaky heart valves and poor systolic and diastolic function. Conventional flow imaging with ultrasound is however limited to only measuring the velocity component along the ultrasound beam, i.e. it is a one-dimensional and angle-dependent measurement. This discrepancy limits the usefulness of Doppler ultrasound in diagnostic settings. In this work we will focus on further developing multi-dimensional flow velocity estimators based on speckle tracking, i.e. image pattern matching techniques. The main clinical application will be pediatric cardiology, with the aim to improve the depiction of complex flow patterns such as vortex and shunt flow.The proposed multidimensional approaches proposed are however not as robust as conventional methods. Thus, the aims of this student project will be to further develop and optimize tracking algorithms within a robust framework based on the predicted motion of flow, for example using a Kalman filter.Aims: Further develop and validate robust tracking algorithms that optimally weight measurement and modelling errors Test the proposed methods on simplified simulations as well as in vivo data from pediatric cardiologyQualifications:Knowledge of digital signal processing and preferably Matlab.Contact:Researcher Lasse Lvstakken, PhD student Solveig Alnes3: Navigated ultrasound imaging 3-D reconstruction of (pulsatile) artery geometry and flowConventional ultrasound imaging of blood flow in central and peripheral arteries is today based on 2-D imaging, while pathology related to atherosclerosis is inherently three-dimensional. While real-time 3-D ultrasound is available for cardiac imaging, transducers for vascular imaging are not yet available. However, by utilizing highly accurate position sensors during scanning, it is possible to reconstruct the 3-D geometry of arteries based on multiple 2-D flow and B-mode images. In this project we will utilize recently installed navigation system based on optical and magnetic sensors to reconstruct 3-D flow in the carotid artery. This flow is highly pulsatile, and we will also incorporate information from ECG (electro-cardiogram) to also get timing information. The imaging approach will follow a recent plane-wave imaging scheme, where a high frame rate and high image quality can be achieved. Investigations will first be done using in vitro setup of known stationary and pulsatile flow. In vivo imaging in healthy volunteers will further be tries to show the potential of mapping arterial geometry and pulsatile 3-D flow patterns.Preferred qualifications:Programming in Matalb and C++Contact:Researcher Lasse Lvstakken, PhD student Daniel H. IversenLink to this Back Cardiac ultrasound Cardiac ultrasoundCardiac ultrasound, also known as echocardiography, concerns the ultrasound imaging of a very fast moving complex organ positioned deep within the body - the heart. In Trondheim, a group of engineers and medical doctors have a more than 30 year history for collaborative efforts on improving the methods for imaging and analysis of the function of the heart.Topic: Myocardial deformationThe heart is a muscle that both pushes blood out and sucks new blood in. In some cardiac diseases, the ability to suck is more reduced than the ability to push because the heart muscle is stiff, and this creates problems for the filling of the heart. The consequence is that the heart pumps less efficiently, and that the patient's exercise capacity is reduced. It is difficult to measure cardiac muscle stiffness directly, but with new ultrasound technology, we can achieve extreme time resolution (> 1000 images per second). Thus we can see mechanical phenomena we have not seen before, such as fast deformation waves.Our hypothesis is that the velocity of these waves is related to cardiac muscle stiffness.The task of this thesis is to develop a finite element model where the propagation of such waves can be simulated. The work will be based on FEM-models already developed at the Dept. of structural engineering.Supervisors:Leif Rune HellevikHans TorpBrage H Amundsen