Biomedical subjects

G Ferrigno

Publications and source records attributed to G Ferrigno.

At least 19 recordsLinked to original sources

PubMed2006

Automatic extraction of the mid-facial plane for cranio-maxillofacial surgery planning.

Recently developed computer applications provide tools for planning cranio-maxillofacial interventions based on 3-dimensional (3D) virtual models of the patient's skull obtained from computed-tomography (CT) scans. Precise knowledge of the location of the mid-facial plane is important for the assessment of deformities and for planning reconstructive procedures. In this work, a new method is presented to automatically compute the mid-facial plane on the basis of a surface model of the facial skeleton obtained from CT. The method matches homologous surface areas selected by the user on the left and right facial side using an iterative closest point optimization. The symmetry plane which best approximates this matching transformation is then computed. This new automatic method was evaluated in an experimental study. The study included experienced and inexperienced clinicians defining the symmetry plane by a selection of landmarks. This manual definition was systematically compared with the definition resulting from the new automatic method: Quality of the symmetry planes was evaluated by their ability to match homologous areas of the face. Results show that the new automatic method is reliable and leads to significantly higher accuracy than the manual method when performed by inexperienced clinicians. In addition, the method performs equally well in difficult trauma situations, where key landmarks are unreliable or absent.

Algorithms↗

PubMed2006

A neural network based method for optical patient set-up registration in breast radiotherapy.

Patient set-up optimization is required in breast-cancer radiotherapy to fill the accuracy gap between personalized treatment planning and uncertainties in the irradiation set-up. Opto-electronic systems allow implementing automatic procedures to minimize the positional mismatches of light-reflecting markers located on the patient surface with respect to a corresponding reference configuration. The same systems are used to detect the position of the irradiated body surface by means of laser spots; patient set-up is then corrected by matching the control points onto a CT based reference model through surface registration algorithms. In this paper, a non-deterministic approach based on Artificial Neural Networks is proposed for the automatic, real-time verification of geometrical set-up of breast irradiation. Unlike iterative surface registration methods, no passive fiducials are used and true real-time performance is obtained. Moreover, the non-deterministic modeling performed by the neural algorithm minimizes sensitivity to intra-fractional and inter-fractional non-rigid motion of the breast. The technique was validated through simulated activities by using reference CT data acquired on four subjects. Results show that the procedure is able to detect and reduce simulated set-up errors and revealed high reliability in patient position correction, even when the surface deformation is included in testing conditions.

Breast Neoplasms↗

PubMed2006

Enhancing digital cephalic radiography with mixture models and local gamma correction.

We present a new algorithm, called the soft-tissue filter, that can make both soft and bone tissue clearly visible in digital cephalic radiographies under a wide range of exposures. It uses a mixture model made up of two Gaussian distributions and one inverted lognormal distribution to analyze the image histogram. The image is clustered in three parts: background, soft tissue, and bone using this model. Improvement in the visibility of both structures is achieved through a local transformation based on gamma correction, stretching, and saturation, which is applied using different parameters for bone and soft-tissue pixels. A processing time of 1 s for 5 Mpixel images allows the filter to operate in real time. Although the default value of the filter parameters is adequate for most images, real-time operation allows adjustment to recover under- and overexposed images or to obtain the best quality subjectively. The filter was extensively clinically tested: quantitative and qualitative results are reported here.

Algorithms↗

PubMed2005

CT-3D rotational angiography automatic registration: a sensitivity analysis.

Preprocessing, binning and dataset subsampling are investigated with regard to simultaneous maximisation of the speed, accuracy and robustness of CT-3D rotational angiography (3DRA) registration. Clinical diagnosis and treatment can both take advantage of this integration, because 3DRA allows the shape of vessel structures to be evaluated three-dimensionally with respect to standard 2D projective angiography. The method for optimising preprocessing, binning and subsampling consisted of independent variation of the corresponding parameters to maximise robustness and speed while maintaining subvoxel accuracy; the latter was computed as the sum of the mean squared errors initially present in the registrations with the errors relative to both binning and subsampling. The results suggest the choice of 256 bins, steps between 14 mm (coarse optimisation) and 2.5 mm (fine optimisation) and bone segmentation by threshold, for binning, subsampling and preprocessing, respectively. The application of this parameter set-up to 50 CT-3DRA registrations resulted in a saving, on average, of 40% of the time with respect to the method previously used, while registration error was maintained within 2 mm (1.97 mm, 90% confidence interval) and robustness was increased, so that no manual initial realignment was needed in 48 registrations. Validation by the registration of images acquired for a head phantom showed subvoxel residual errors. In conclusion, the proposed procedure can be considered a satisfactory strategy to optimise CT-3DRA registration.

Angiography↗

PubMed2005

Derivation of centers and axes of rotation for wrist and fingers in a hand kinematic model: methods and reliability results.

In the field of 3D reconstruction of human motion from video, model-based techniques have been proposed to increase the estimation accuracy and the degree of automation. The feasibility of this approach is strictly connected with the adopted biomechanical model. Particularly, the representation of the kinematic chain and the assessment of the corresponding parameters play a relevant role for the success of the motion assessment. In this paper, the focus is on the determination of the kinematic parameters of a general hand skeleton model using surface measurements. A novel method that integrates nonrigid sphere fitting and evolutionary optimization is proposed to estimate the centers and the functional axes of rotation of the skeletal joints. The reliability of the technique is tested using real movement data and simulated motions with known ground truth 3D measurement noise and different ranges of motion (RoM). With respect to standard nonrigid sphere fitting techniques, the proposed method performs 10-50% better in the best condition (very low noise and wide RoM) and over 100% better with physiological artifacts and RoM. Repeatability in the range of a couple of millimeters, on the localization of the centers of rotation, and in the range of one degree, on the axis directions is obtained from real data experiments.

Adult↗

PubMed2005

Preliminary study on the use of nonrigid registration for thoraco-abdominal radiosurgery.

The inclusion of organ deformation and movement in radiosurgery treatment planning is of increasing importance as research and clinical applications begin to take into consideration the effects of physiological processes, like breathing, on the shape and position of lesions. In this scenario, the challenge is to localize the target in toto (not only by means of marker sampling) and to calculate the dose distribution as the sum of all the contributions from the positions assumed by the target during the respiratory cycle. The aim of this work is to investigate the use of nonrigid registration for target tracking and dynamic treatment planning, i.e., treatment planning based not on one single CT scan but on multiple CT scans representative of the respiration. Twenty patients were CT scanned at end-inhale and end-exhale. An expert radiation oncologist identified the PTV in both examinations. The two CT data sets per patient were nonrigidly registered using a free-form deformation algorithm based on B-splines. The optimized objective function consisted of a weighted sum of a similarity criterion (Mutual Information) and a regularization factor which constrains the transformation to be locally rigid. Once the transformation was obtained and the registration validated, its parameters were applied to the target only. Finally, the deformed target was compared to the PTV delineated by the radiation oncologist in the other study. The results of this procedure show an agreement between the center of mass as well as volume of the target identified automatically by deformable registration and manually by the radiation oncologist. Moreover, obtained displacements were in agreement with body structure constraints and considerations usually accepted in radiation therapy practice. No significant influence of initial target volume on displacements was found. In conclusion, the proposed method seems to offer the possibility of using nonrigid registrations in radiosurgery treatment planning, even if more cases need to be investigated in order to give a statistical consistency to parameter setup and proposed considerations.

Abdominal Neoplasms↗

PubMed2004

Kinematical models to reduce the effect of skin artifacts on marker-based human motion estimation.

The estimation of the skeletal motion obtained from marker-based motion capture systems is known to be affected by significant bias caused by skin movement artifacts, which affects joint center and rotation axis estimation. Among different techniques proposed in the literature, that based on rigid body model, still the most used by commercial motion capture systems, can smooth only part of the above effects without eliminating their main components. In order to sensibly improve the accuracy of the motion estimation, a novel technique, named local motion estimation (LME), is proposed. This rests on a recently described approach that, using virtual humans and extended Kalman filters, estimates the kinematical variables directly from 2D measurements without requiring the 3D marker reconstruction. In this paper, we show how such method can be extended to include the computation of the local marker displacement due to skin artifacts. The 3D marker coordinates, expressed in the corresponding local reference coordinate frames, are inserted into the state vector of the filter and their dynamics is automatically estimated, with adequate accuracy, without assuming any particular deformation function. Simulated experiments of lower limb motion, involving systematic mislocations (5, 10, 20 mm) and random errors of the marker coordinates and joint center locations (+/-5, +/-10, +/-15 mm), have shown that artifact motion can be substantially decoupled from the global skeletal motion with an effective increase of the accuracy wrt standard techniques. In particular, the comparison between the nominal kinematical variables and the one recovered from markers attached to the skin surface proved LME to be sensibly superior (50% in the worse condition) to the methods imposing marker-bone rigidity. In conclusion, while requiring further validation on real movement data, we argue that the proposed method can constitute an appropriate approach toward the improvement of the human motion estimation.

Biomechanical Phenomena↗

PubMed2004

Model of head-neck joint fast movements in the frontal plane.

The objective of this work is to develop a model representing the physiological systems driving fast head movements in frontal plane. All the contributions occurring mechanically in the head movement are considered: damping, stiffness, physiological limit of range of motion, gravitational field, and muscular torques due to voluntary activation as well as to stretch reflex depending on fusal afferences. Model parameters are partly derived from the literature, when possible, whereas undetermined block parameters are determined by optimising the model output, fitting to real kinematics data acquired by a motion capture system in specific experimental set-ups. The optimisation for parameter identification is performed by genetic algorithms. Results show that the model represents very well fast head movements in the whole range of inclination in the frontal plane. Such a model could be proposed as a tool for transforming kinematics data on head movements in 'neural equivalent data', especially for assessing head control disease and properly planning the rehabilitation process. In addition, the use of genetic algorithms seems to fit well the problem of parameter identification, allowing for the use of a very simple experimental set-up and granting model robustness.

Adult↗

PubMed2004

Evolutionary optimization for robust hierarchical computation of the rotation centres of kinematic chains from reduced ranges of motion the lower spine case.

A novel technique based on evolutionary optimization is proposed here to compute the average rotation centres (RCs) of ball joints linked into kinematic chains using 3D trajectories of the markers attached to the external surface of the corresponding articulated structures. The chain is hierarchically solved by iteratively minimizing the variance of the marker distances from the actual RC through an evolutional strategy method (ESM) from proximal to distal joints. In particular, the technique is compared to the non-rigid sphere-fitting method, recently proposed in literature and implemented through a closed-form solution (CFS), in conditions of random and systematic noise superimposed to the marker coordinates. Results from simulated motions showed that, in case of small range of motion (5 degrees , 10 degrees ) the performance of CFS is really unreliable whereas ESM provided satisfactory accuracy. Error propagation along the kinematic chain was found to be negligible. Also in the case of systematic errors, ESM provides an accuracy that is sensibly better than that of the CFS. As a case study, ESM was applied to the in vivo computation of the RCs of the vertebrae in the lower spine region using a specific marker protocol. A set of spine movements by a normal adult male, recorded by an optoelectronic motion capture system, were processed with the developed method. The variability of the estimated average RCs was small (few millimeters) in agreement with the literature data from cadaveric studies and X-ray imaging.

Algorithms↗

PubMed2004

Non-invasive approach towards the in vivo estimation of 3D inter-vertebral movements: methods and preliminary results.

A kinematical model of the lower spine was designed and used to obtain a robust estimation of the vertebral rotations during torso movements from skin-surface markers recorded by video-cameras. Markers were placed in correspondence of the anatomical landmarks of the pelvic bone and vertebral spinous and transverse processes, and acquired during flexion, lateral bending and axial motions. In the model calibration stage, a motion-based approach was used to compute the rotation axes and centres of the functional segmental units. Markers were mirrored into virtual points located on the model surface, expressed in the local reference system of coordinates. The spine motion assessment was solved into the domain of extended Kalman filters: at each frame of the acquisition, the model pose was updated by minimizing the distances between the measured 2D marker projections on the cameras and the corresponding back-projections of virtual points located on the model surface. The novelty of the proposed technique rests on the fact that the varying location of the rotation centres of the functional segmental units can be tracked directly during motion computation. In addition, we show how the effects of skin artefacts on orientation data can be taken into account. As a result, the kinematical estimation of simulated motions shows that orientation artefacts were reduced by a factor of at least 50%. Preliminary experiments on real motion confirmed the reliability of the proposed method with results in agreement with classical studies in literature.

Algorithms↗

PubMed2004

ELITE-S2: the multifactorial movement analysis facility for the International Space Station.

Experimental observations of adaptation processes of the motor control system to altered gravity conditions can provide useful elements to the investigations on the mechanisms underlying motor control of human subject. The microgravity environment obtained on orbital flights represents a unique experimental condition for the monitoring of motor adaptation. The research in motor control exploits the changes caused by microgravity on the overall sensorimotor process, due to the impairment of the sensory systems whose function depends upon the presence of the gravity vector. Motor control in microgravity has been investigated during parabolic flights and short-term space missions, in particular for analysis of movement-posture co-ordination when equilibrium is no longer a constraint. Analysis of long-term adaptation would also be very interesting, calling for long-term body motion observations during the process of complete motor adaptation to the weightlessness environment. ELITE-S2 is an innovative facility for quantitative human movement analysis in weightless conditions onboard the International Space Station (ISS). ELITE-S2 is being developed by the Italian Space Agency, ASI is to be delivering the flight models to NASA to be included in an expressed rack in US Lab Module in February 2004. First mission is currently planned for summer 2004 (increment 10 ULF 2 ISS).

Adaptation, Physiological↗

PubMed2003

Real-time human motion estimation using biomechanical models and non-linear state-space filters.

In the field of sports biomechanics and rehabilitation engineering, the possibility of computing, in real time, the angular displacements and derivatives of human joints, from a video of motion sequences, represents an appealing goal. In particular, applications of biofeedback protocols in rehabilitation can benefit from this capability. The focus of the investigation was concerned with the application of biomechanical models, comprising of a kinematic chain and surface envelopes, and state-space filters, to the computation, in real time and with high accuracy, of the angular data and derivatives. By minimising the distances, measured with TV cameras, between the 2D marker projections and the corresponding back-projected markers located on the mannequin, the configuration of the biomechanical model was automatically updated. The use of state-space estimation allowed the computation of smooth derivatives of the orientation data. Owing to the non-linearity of the functions involved, the derivatives of the observation model were obtained through a multidimensional extension of Stirling's interpolation formula. Proper algorithms were developed to cope with the model calibration, initialisation and data labelling. Extensive experiments on real and simulated motions proved the reliability (maximum angular error less than 1 degree, maximum point reconstruction less than 1 mm) of the developed system, which is robust to false matching caused by marker occlusions. Moreover, orientation artifacts due to skin motion can be reduced by a factor of 50%.

Algorithms↗

PubMed2003

Hierarchical radial basis function networks and local polynomial un-warping for X-ray image intensifier distortion correction: a comparison with global techniques.

Global polynomial (GP) methods have been widely used to correct geometric image distortion of small-size (up to 30 cm) X-ray image intensifiers (XRIIs). This work confirms that this kind of approach is suitable for 40 cm XRIIs (now increasingly used). Nonetheless, two local methods, namely 3rd-order local un-warping polynomials (LUPs) and hierarchical radial basis function (HRBF) networks are proposed as alternative solutions. Extensive experimental tests were carried out to compare these methods with classical low-order local polynomial and GP techniques, in terms of residual error (RMSE) measured at points not used for parameter estimation. Simulations showed that the LUP and HRBF methods had accuracies comparable with that attained using GP methods. In detail, the LUP method (0.353 microm) performed worse than HRBF (0.348 microm) only for small grid spacing (15 x 15 control points); the accuracy of both HRBF (0.157 microm) and LUP (0.160 microm) methods was little affected by local distortions (30 x 30 control points); weak local distortions made the GP method poorer (0.320 microm). Tests on real data showed that LUP and HRBF had accuracies comparable with that of GP for both 30 cm (GP: 0.238 microm; LUP: 0.240 microm; HRBF: 0.238 microm) and 40 cm (GP: 0.164 microm; LUP: 0.164 microm; HRBF: 0.164 microm) XRIIs. The LUP-based distortion correction was implemented in real time for image correction in digital tomography applications.

Algorithms↗

PubMed2003

Evaluation of methods for opto-electronic body surface sensing applied to patient position control in breast radiation therapy.

The accuracy gap between the high levels of accuracy in radiotherapy planning and the uncertain set-up of each therapy fraction represents a crucial factor in the optimisation of radiation treatment. This occurs because the conventional means of patient alignment and immobilisation do not guarantee accurate implementation of the therapy plan in the actual irradiation treatment. A patient repositioning technique is proposed, based on opto-electronic motion capture and on methods of registration of body surfaces described by a limited dataset. The validation of the method was related to breast cancer radiotherapy and was based on simulated and experimental repositioning procedures involving a phantom and two subjects. With respect to previous work, the surface registration procedure was, in this case, implemented as a constrained non-linear least-square problem (constraints were given by the position of a couple of passive markers placed on the sternum), and three different algorithms were compared in terms of accuracy in misalignment detection and of computational cost. The simulation and experimental activities identified the best performing algorithm, which systematically limited the repositioning errors to below clinically acceptable thresholds (5 mm), with residual surface mismatches lower than 2 mm.

Algorithms↗

PubMed2003

Robust recovery of human motion from video using Kalman filters and virtual humans.

In sport science, as in clinical gait analysis, optoelectronic motion capture systems based on passive markers are widely used to recover human movement. By processing the corresponding image points, as recorded by multiple cameras, the human kinematics is resolved through multistage processing involving spatial reconstruction, trajectory tracking, joint angle determination, and derivative computation. Key problems with this approach are that marker data can be indistinct, occluded or missing from certain cameras, that phantom markers may be present, and that both 3D reconstruction and tracking may fail. In this paper, we present a novel technique, based on state space filters, that directly estimates the kinematical variables of a virtual mannequin (biomechanical model) from 2D measurements, that is, without requiring 3D reconstruction and tracking. Using Kalman filters, the configuration of the model in terms of joint angles, first and second order derivatives is automatically updated in order to minimize the distances, as measured on TV-cameras, between the 2D measured markers placed on the subject and the corresponding back-projected virtual markers located on the model. The Jacobian and Hessian matrices of the nonlinear observation function are computed through a multidimensional extension of Stirling's interpolation formula. Extensive experiments on simulated and real data confirmed the reliability of the developed system that is robust against false matching and severe marker occlusions. In addition, we show how the proposed technique can be extended to account for skin artifacts and model inaccuracy.

Humans↗

PubMed2002

Self-marking of anatomical landmarks for on-orbit experimental motion analysis compared to expert direct-marking.

The on-orbit application of movement analysis methodology, on-board space stations, for studying the gravity role in motor functions, requires a careful adaptation of the currently adopted techniques in order to obtain reliable data. In those operative conditions, differently from common on-ground experimental activities, a non-specialist operator, an astronaut of the space station crew, is expected to self-administer the experimental protocol, particularly self-marking specific anatomical landmarks. The present paper proposes a movement analysis methodology, which fits the specific constraints of space activity and matches the objective of maximising reliability and minimising on-orbit time, and reports normative data about accuracy and precision of the self-marking of an extended set of anatomical landmarks. The same set of landmarks has been considered also for direct-marking performed by experts in motion analysis and their results have been compared to self-marking ones. The paper contents will support the design of future space experimental campaigns and is, in general, applicable to any on-ground scientific investigation, possibly increasing data reliability.

Adult↗

PubMed2002

Distortion correction for x-ray image intensifiers: local unwarping polynomials and RBF neural networks.

In this paper we present two novel techniques, namely a local unwarping polynomial (LUP) and a hierarchical radial basis function (HRBF) network, to correct geometric distortions in XRII images. The two techniques have been implemented and compared, in terms of residual error measured at control and intermediate points, with local and global methods reported in the previous literature. In particular, LUP rests on a locally optimized 3rd degree polynomial applied within each quadrilateral cell on the rectilinear calibration grid of points. HRBF, based on a feed-forward neural network paradigm, is constituted by a set of hierarchical layers at increasing cut-off frequency, each characterized by a set of Gaussian functions. Extensive experiments have been performed both on simulated and real data. In simulation, we tested the effect of pincushion, sigmoidal and local distortions, along with the number of calibration points. Provided that a sufficient number of cells of the calibration grid is available, the obtained accuracy for both LUP and HRBF is comparable to or better than that of global polynomial technique. Tests on real data, carried out by using two different (12 in. and 16 in.) XRIIs, showed that the global polynomial accuracy (0.16+/-0.08 pixels) is slightly worse than that of LUP (0.07+/-0.05 pixels) and HRBF (0.08+/-0.04 pixels). The effects of the discontinuity at the border of the local areas and the decreased accuracy at intermediate points, typical of local techniques, have been proved to be smoothed for both LUP and HRBF.

Algorithms↗

PubMed2002

Euromir 95 T4 experiment 'Human Posture in microgravity': global results and future perspectives.

After 7 years of studies on Euromir 95 T4 experiment 'Human Posture in microgravity' dataset, some important remarks can be proposed for best exploiting future experimental campaigns as well as for neurophysiological investigations on-ground. The main focus of such experiments was to monitor the process of learning and adapting to the new environment in performing complex voluntary movements. Euromir 95 was the first quantitative investigation with high technology instrumentation (ELITE-S) involving two subjects starting from 15 days after the launch until 5 months of mission. Results confirm the excellent capability of mutation of motor planning by the central nervous system (CNS) in order to best exploit environmental constraints and advantages. Under this view, the results offer a unique cue for improving the design of rehabilitation processes in motor pathologies.

Journal Article↗