R. J. Lapeer

Fetal head moulding: finite element analysis of a fetal skull subjected to uterine pressures during the first stage of labour

Fetal head moulding is a phenomenon which may contribute to satisfactory progress during delivery as it allows the fetal head to accommodate to the geometry of the passage. In contrast, excessive head moulding may result in cranial birth injuries and thus affect the infant shortly or even long after birth. One group of researchers in the past investigated the biomechanics of fetal head moulding from an engineering point of view and limited themselves to a static, linear model of the parietal bones. In this paper, we present a non-linear model of the deformation of a complete fetal skull, when subjected to pressures exerted by the cervix, during the first stage of labour. The design of the model involves four main steps: shape recovery of the fetal skull, the generation of a valid and compatible mesh for finite element analysis (FEA), the specification of a physical model and the analysis of deformation. Results of the analysis show good agreement with those obtained from clinical experiments on the quantitative assessment of fetal head moulding. The model also displays shapes after moulding which have been reported in previous studies and which are generally known in the obstetric and paediatric communities.

Simulating plastic surgery: From human skin tensile tests, through hyperelastic finite element models to real-time haptics

In this paper, we provide a summary of a number of experiments we conducted to arrive at a prototype real-time simulator for plastic surgical interventions such as skin flap repair and inguinal herniotomy. We started our research with a series of in-vitro tensile stress tests on human skin, harvested from female patients undergoing plastic reconstructive surgery. We then used the acquired stress-strain data to fit hyperelastic models. Three models were considered: General Polynomial, Reduced Polynomial and Ogden. Only Reduced Polynomial models were found to be stable, hence they progressed to the next stage to be used in an explicit finite element model aimed at real-time performance in conjunction with a haptic feedback device. A total Lagrangian formulation with the half-step central difference method was employed to integrate the dynamic equation of motion of the mesh. The mesh was integrated into two versions of a real-time skin simulator: a single-threaded version running on a computers main central processing unit and a multi-threaded version running on the computers graphics card. The latter was achieved by exploiting recent advances in programmable graphics technology.

Image-enhanced surgical navigation for endoscopic sinus surgery: evaluating calibration, registration and tracking

Endoscopic sinus surgery (ESS) is generally applied to treat sinusitis when medication is not effective in eliminating the symptoms. Images captured by the endoscope are viewed on a monitor placed near the surgeon. Due to the separation of the handling of the endoscope from the viewing of the image, ESS requires surgeons to have well‐trained hand–eye coordination. Unlike the use of the stereo surgical microscope in ENT, the endoscope does not provide the stereo cue for depth perception, hence a surgeon can only perceive depth through motion and shading, which may affect the accuracy of tool placement. Whilst the skill and experience of the surgeon are important factors to the success of ESS, the assistance of image‐enhanced surgical navigation (IESN) can further reassure the surgeons judgement and enhance surgical performance.

An augmented reality based simulation of obstetric forceps delivery

During the process of human childbirth, obstetric forceps delivery is a justified alternative to Caesarean section when vaginal delivery proves difficult or impossible. Currently, training of forceps interventions is done on a real case due to the lack of realistic dummy models. This paper presents a basic augmented reality implementation of a forceps delivery which provides a platform for both training of forceps placement and manipulation for junior obstetricians as well as the assessment of any mechanical effects these actions may have on the fetus, and the fetal head and skull in particular.

Active Watersheds: Combining 3D Watershed Segmentation and Active Contours to Extract Abdominal Organs from MR Images

The three-dimensional segmentation of regions of interest in medical images, be it a 2D slice by slice based approach or directly across the 3D dataset, has numerous applications for the medical professional. These applications may involve something as simple as visualisation up to more critical tasks such as volume estimation, tissue quantification and classification, the detection of abnormalities and more. In this paper we describe a method which aims to combine two of the more popular segmentation techniques: the watershed segmentation and the active contour segmentation. Watershed segmentation provides unique boundaries for a particular image or series of images but does not easily allow for the discrete nature of the image and the image noise. Active contours or snakes do possess this generalisation or smoothing property but are difficult to initialise and usually require to be close to the boundary of interest to converge. We present a hybrid approach by segmenting a region of interest (ROI) using a 3D marker-based watershed algorithm. The resulting ROIs boundaries are then converted into a contour, using a contour following algorithm which is explained during the course of the paper. Once the contours are determined, different parameter settings of internal/external forces allow the expert user to adapt the initial segmentation. The approach thus yields a fast initial segmentation from the watershed algorithm and allows fine-tuning using active contours. Results of the technique are illustrated on 3D colon, kidney and liver segmentations from MRI datasets.

Application of neural networks to the ranking of perinatal variables influencing birthweight

In this paper we compare Multi-Layer Perceptrons (a neural network type) with Multivariate Linear Regression in predicting birthweight from nine perinatal variables which are thought to be related. Results show, that seven of the nine variables, i.e., gestational age, mothers body-mass index (BMI), sex of the baby, mothers height, smoking, parity and gravidity, are related to birthweight. We found no significant relationship between birthweight and each of the two variables, i.e., maternal age and social class.

PC-based volume rendering for medical visualisation and augmented reality based surgical navigation

We describe a generic software architecture for stereoscopic augmented reality microsurgery, built upon a general framework for volume rendering based 3D visualisation. The software is called ARView and allows the user to perform the standard procedures for stereoscopic augmented reality surgical navigation: calibration of a visualisation device; registration of pre-operatively and intra-operatively acquired patient image data; overlaying with either volume or surface rendered (segmented) data using different methodologies; and tracking of moving objects in the surgical scene.

Physics-based animation of a trotting horse in a virtual environment

In this paper we describe the implementation of a physics-based animation of a trotting horse in real-time. The horse is modelled as a collection of connected bodies using the open dynamics engine library to simulate gravity. The animation is created by comparing the current state of the horse with a desired state and applying torques proportionally to the errors present between the two. The desired state is obtained from frames of video footage of a trotting horse. P-controllers are used to minimise the error between current and desired angle positions as well as global positioning and orientation of the horses trajectory. Results show realistic movement patterns as compared to the video footage and realistic ground reaction force patterns of each individual leg.

Using a passive coordinate measurement arm for motion tracking of a rigid endoscope for augmented reality image guided surgery

One of the main sources of error in commercial surgical navigation systems is the tracking of surgical tools. Mainstream systems typically use optical or electromagnetic tracking technologies, which exhibit accuracies of the order of 1 mm. The objective of this study was to introduce a lightweight high‐precision passive coordinate measurement arm into an augmented reality‐based surgical navigation system to track a rigid endoscope.

Computer Assisted ENT Surgery Using Augmented Reality: Preliminary Results on the CAESAR Project

The ‘Computer Assisted ENT Surgery using Augmented Reality’ (CAESAR) project aims to improve ENT surgical procedures through augmentation of the real operative scene during surgery: a virtual scene, which shows structures that are normally hidden to the eye of the surgeon, is superimposed onto the real scene. The main distinction of this project as opposed to previous work in the field is to create a hierarchical and stepwise implemented system which allows operations such as calibration, tracking and registration to be assessed on an individual basis. This allows us to compare different alternatives for each operation and eventually apply the best solution without interfering with the performance of other parts of the system. In this paper, we present a framework for the alignment of the objects/subject in the real and virtual operating environment before the onset of surgery, and test its performance on a phantom skull. The operations involved are thus based on a static system and include calibration of the stereo microscope and registration of the virtual patient (as reconstructed from CT data) with the real patient. The final alignment of all objects in the real and virtual operating scene is assessed by cumulating maximum errors of each individual step.