Catálogo de publicaciones - libros

This paper describes the construction of simulated SPECT and MRI databases that account for realistic anatomical and functional variability. The data is used as a gold-standard to evaluate four SPECT/MRI similarity-based registration methods.

Simulation realism was accounted for using accurate physical models of data generation and acquisition. MRI and SPECT simulations were generated from three subjects to take into account inter-subject anatomical variability. Functional SPECT data were computed from six functional models of brain perfusion. Previous models of normal perfusion and ictal perfusion observed in Mesial Temporal Lobe Epilepsy (MTLE) were considered to generate functional variability. We studied the impact noise and intensity non-uniformity in MRI simulations and SPECT scatter correction may have on registration accuracy.

We quantified the amount of registration error caused by anatomical and functional variability. Registration involving ictal data was less accurate than registration involving normal data. MR intensity non-uniformity was the main factor decreasing registration accuracy. The proposed simulated database is promising to evaluate many functional neuroimaging methods, involving MRI and SPECT data.

In radiotherapy, the constant margin taken around the visible tumor is a very coarse approximation of the invasion margin of cancerous cells. In this article, a new formulation to estimate the invasion margin of a tumor by extrapolating low tumor densities in magnetic resonance images (MRIs) is proposed. The current imaging techniques are able to show parts of the tumor where cancerous cells are dense enough. However, tissue parts containing small number of tumor cells are not enhanced in images. We propose a way to estimate these parts using the tumor mass visible in the image. Our formulation is based on the Fisher-Kolmogorov Equation that is been widely used to model the growth of brain tumors. As a proof of concept, we show some promising preliminary results, which demonstrate the feasibility of the approach.

Minimally Invasive Surgery (MIS) has recognized benefits of reduced patient trauma and recovery time. In practice, MIS procedures present a number of challenges due to the loss of 3D vision and the narrow field-of-view provided by the camera. The restricted vision can make navigation and localization within the human body a challenging task. This paper presents a robust technique for building a repeatable long term 3D map of the scene whilst recovering the camera movement based on Simultaneous Localization and Mapping (SLAM). A sequential vision only approach is adopted which provides 6 DOF camera movement that exploits the available textured surfaces and reduces reliance on strong planar structures required for range finders. The method has been validated with a simulated data set using real MIS textures, as well as MIS video sequences. The results indicate the strength of the proposed algorithm under the complex reflectance properties of the scene, and the potential for real-time application for integrating with the existing MIS hardware.

With the advancement of minimally invasive techniques for surgical and diagnostic procedures, there is a growing need for the development of methods for improved visualization of internal body structures. Video mosaicking is one method for doing this. This approach provides a broader field of view of the scene by stitching together images in a video sequence. Of particular importance is the need for online processing to provide real-time feedback and visualization for image-guided surgery and diagnosis. We propose a method for online video mosaicking applied to endoscopic imagery, with examples in microscopic retinal imaging and catadioptric endometrial imaging.

The idea of in-situ visualization for surgical procedures has been widely discussed in the community [1,2,3,4]. While the tracking technology offers nowadays a sufficient accuracy and visualization devices have been developed that fit seamlessly into the operational workflow [1,3], one crucial problem remains, which has been discussed already in the first paper on medical augmented reality [4]. Even though the data is presented at the correct place, the physician often perceives the spatial position of the visualization to be closer or further because of virtual/real overlay.

This paper describes and evaluates novel visualization techniques that are designed to overcome misleading depth perception of trivially superimposed virtual images on the real view. We have invited 20 surgeons to evaluate seven different visualization techniques using a head mounted display (HMD). The evaluation has been divided into two parts. In the first part, the depth perception of each kind of visualization is evaluated quantitatively. In the second part, the visualizations are evaluated qualitatively in regard to user friendliness and intuitiveness. This evaluation with a relevant number of surgeons using a state-of-the-art system is meant to guide future research and development on medical augmented reality.

Several visualization methods for intraoperative navigation systems were proposed in the past. In standard slice based navigation, three dimensional imaging data is visualized on a two dimensional user interface in the surgery room. Another technology is the in-situ visualization i.e. the superimposition of imaging data directly into the view of the surgeon, spatially registered with the patient. Thus, the three dimensional information is represented on a three dimensional interface. We created a hybrid navigation interface combining an augmented reality visualization system, which is based on a stereoscopic head mounted display, with a standard two dimensional navigation interface. Using an experimental setup, trauma surgeons performed a drilling task using the standard slice based navigation system, different visualization modes of an augmented reality system, and the combination of both. The integration of a standard slice based navigation interface into an augmented reality visualization overcomes the shortcomings of both systems.

In this paper, we propose a new visualization technique for virtual colonoscopy (VC). The proposed method is called , which splits the entire colon anatomy into exactly two halves. Then, it assigns a virtual camera to each half to perform fly-over navigation, which has several advantages over both traditional fly-through and related methods. First, by controlling the elevation of the camera, there is no restriction on its field of view (FOV) angle (e.g., >90) to maximize visualized surface areas, and hence no perspective distortion. Second, the camera viewing volume is perpendicular to each colon half, so potential polyps that are hidden behind haustral folds are easily found. Finally, because the orientation of the splitting surface is controllable, the navigation can be repeated at a different split orientation to overcome the problem of having a polyp that is divided between the two halves of the colon. Quantitative experimental results on 15 clinical datasets have shown that the average surface visibility coverage is 99.59±0.2%.

We present an ultrasound vibro-elastography system designed to acquire viscoelastic properties of the prostate and peri-prostatic tissue. An excitation stage imparts low-frequency (<20 Hz), limited amplitude (<± 2mm), broadband vibratory motion to an endorectal transducer, along a radial/transversal direction. The induced tissue motion is estimated from ultrasound radio-frequency data and is used to estimate the mechanical frequency response of tissue to the excitation at different spatial locations. This can be used to determine the spatial distribution of various mechanical parameters of tissue, such as stiffness and viscosity. Phantom and images are presented. The results obtained demonstrate high phantom and tissue linearity and high signal-to-noise ratio.

The importance of accurate attenuation correction in single photon emission computed tomography (SPECT) has been widely recognized. In this paper, we propose a novel scheme of simultaneous reconstruction of the tissue attenuation map and the radioactivity distribution from SPECT emission sinograms, which is obviously beneficial when the transmission data is missing for cost or efficiency reasons. Our strategy combines the SPECT image formation and data measurement models, whereas the attenuation parameters are treated as random variables with known prior statistics. After converting the models to state space representation, the extended Kalman filtering procedures are adopted to linearize the equations and to provide the joint estimates in an approximate optimal sense. Experiments have been performed on synthetic data and real scanning data to illustrate abilities and benefits of the method.

We present a framework for statistical finite element analysis combining shape and material properties, and allowing performing statistical statements of biomechanical performance across a given population. In this paper, we focus on the design of orthopaedic implants that fit a maximum percentage of the target population, both in terms of geometry and biomechanical stability. CT scans of the bone under consideration are registered non-rigidly to obtain correspondences in position and intensity between them. A statistical model of shape and intensity (bone density) is computed by means of principal component analysis. Afterwards, finite element analysis (FEA) is performed to analyse the biomechanical performance of the bones. Realistic forces are applied on the bones and the resulting displacement and bone stress distribution are calculated. The mechanical behaviour of different PCA bone instances is compared.