Catálogo de publicaciones - libros

An atlas-based automated liver segmentation method from 3D CT images is described. The method utilizes two types of atlases, that is, the probabilistic atlas (PA) and statistical shape model (SSM). Voxel-based segmentation with PA is firstly performed to obtain a liver region, and then the obtained region is used as the initial region for subsequent SSM fitting to 3D CT images. To improve reconstruction accuracy especially for largely deformed livers, we utilize a multi-level SSM (ML-SSM). In ML-SSM, the whole shape is divided into patches, and principal component analysis is applied to each patches. To avoid the inconsistency among patches, we introduce a new constraint called the adhesiveness constraint for overlap regions among patches. In experiments, we demonstrate that segmentation accuracy improved by using the initial region obtained with PA and the introduced constraint for ML-SSM.

This paper presents a new atlas-based segmentation framework for the delineation of major regions in magnetic resonance brain images employing an atlas of the global topological structure as well as a statistical atlas of the regions of interest. A segmentation technique using fast marching methods and tissue classification is proposed that guarantees strict topological equivalence between the segmented image and the atlas. Experimental validation on simulated and real brain images shows that the method is accurate and robust.

As demands on hospital efficiency increase, there is a stronger need for automatic analysis, recovery, and modification of surgical workflows. Even though most of the previous work has dealt with higher level and hospital-wide workflow including issues like document management, workflow is also an important issue within the surgery room. Its study has a high potential, e.g., for building context-sensitive operating rooms, evaluating and training surgical staff, optimizing surgeries and generating automatic reports.

In this paper we propose an approach to segment the surgical workflow into phases based on temporal synchronization of multidimensional state vectors. Our method is evaluated on the example of laparoscopic cholecystectomy with state vectors representing tool usage during the surgeries. The discriminative power of each instrument in regard to each phase is estimated using AdaBoost. A boosted version of the Dynamic Time Warping (DTW) algorithm is used to create a surgical reference model and to segment a newly observed surgery. Full cross-validation on ten surgeries is performed and the method is compared to standard DTW and to Hidden Markov Models.

In functional connectivity analysis, networks of interest are defined based on correlation with the mean time course of a user-selected ‘seed’ region. In this work we propose to simultaneously estimate the optimal representative time courses that summarize the fMRI data well and the partition of the volume into a set of disjoint regions that are best explained by these representative time courses. Our approach offers two advantages. First, is removes the sensitivity of the analysis to the details of the seed selection. Second, it substantially simplifies group analysis by eliminating the need for a subject-specific threshold at which correlation values are deemed significant. This unsupervised technique generalizes connectivity analysis to situations where candidate seeds are difficult to identify reliably or are unknown. Our experimental results indicate that the functional segmentation provides a robust, anatomically meaningful and consistent model for functional connectivity in fMRI.

We present a robotically assisted prostate brachytherapy system and test results in training phantoms. The system consists of a transrectal ultrasound (TRUS) and a spatially co-registered robot integrated with an FDA-approved commercial treatment planning system. The salient feature of the system is a small parallel robot affixed to the mounting posts of the template. The robot replaces the template interchangeably and uses the same coordinate system. Established clinical hardware, workflow and calibration are left intact. In these experiments, we recorded the first insertion attempt without adjustment. All clinically relevant locations were reached. Non-parallel needle trajectories were achieved. The pre-insertion transverse and rotational errors (measured with Polaris optical tracker relative to the template’s coordinate frame) were 0.25mm (STD=0.17mm) and 0.75° (STD=0.37°). The needle tip placement errors measured in TRUS were 1.04mm (STD=0.50mm). The system is in Phase-I clinical feasibility and safety trials, under Institutional Review Board approval.

Multi-modality fusion imaging for targeted prostate biopsy is difficult because of prostate motion during the biopsy procedure. A closed-loop control mechanism is proposed to improve the efficacy and safety of the biopsy procedure, which uses real-time ultrasound and spatial tracking as feedback to adjust the registration between a preoperative 3D image (e.g. MRI) and real-time ultrasound images. The spatial tracking data is used to initialize the image-based registration between intraoperative ultrasound images and a preoperative ultrasound volume. The preoperative ultrasound volume is obtained using a 2D sweep and manually registered to the MRI dataset before the biopsy procedure. The accuracy of the system is 2.3±0.9 mm in phantom studies. The results of twelve patient studies show that prostate motion can be effectively compensated using closed-loop control.

The fusion of 3D freehand ultrasound with CT and CTA has benefits for a variety of clinical applications, however a lot of manual work is usually required for correct registration. We developed new methods that allow one to simulate medical ultrasound from CT in real-time, reproducing the majority of ultrasonic imaging effects. The second novelty is a robust similarity measure that assesses the correlation of a combination of multiple signals extracted from CT with ultrasound, without knowing the influence of each signal. This serves as the foundation of a fully automatic registration, which aligns a freehand ultrasound sweep with the corresponding 3D modality using a rigid or an affine transformation model, without any manual interaction. We also present the used initialization, global and local parameter optimization schemes, and validation on abdominal CTA and ultrasound imaging of 10 patients.

A 1.5 mm magnetic sphere was navigated automatically inside the carotid artery of a living swine. The propulsion force, tracking and real-time capabilities of a Magnetic Resonance Imaging (MRI) system were integrated into a closed loop control platform. The sphere was released using an endovascular catheter approach. Specially developed software is responsible for the tracking, propulsion, event timing and closed loop position control in order to follow a 10 roundtrips preplanned trajectory on a distance of 5 cm inside the right carotid artery of the animal. Experimental protocol linking the technical aspects of this assay is presented. In the context of this demonstration, many challenges which provide insights about concrete issues of future nanomedical interventions and interventional platforms have been identified and addressed.

The assessment and diagnosis of breast cancer with ultrasound is a challenging problem due to the low contrast between cancer masses and benign tissue. Due to this low contrast it has proven to be difficult to achieve reliable segmentation results on breast cancer masses. An autoregressive model has been employed to filter out of the backscattered RF-signal from a tissue harmonic image which is not degraded by harmonic leakage. Measurements on the filtered image have shown a significant (up to 45 %) increase in contrast between cancer masses and benign tissue.

This paper introduces an outlier rejection and signal reconstruction method for high angular resolution diffusion weighted imaging. The approach is based on the thresholding of Laplacian measurements over the sphere of the apparent diffusion coefficient profiles defined for a given set of gradient directions. Exemplary results are presented.