A new system for computer-aided preoperative planning and intraoperative navigation during corrective jaw surgery

A new system for computer-aided corrective surgery of the jaws has been developed and introduced clinically. It combines three-dimensional (3-D) surgical planning with conventional dental occlusion planning. The developed software allows simulating the surgical correction on virtual 3-D models of the facial skeleton generated from computed tomography (CT) scans. Surgery planning and simulation include dynamic cephalometry, semi-automatic mirroring, interactive cutting of bone and segment repositioning. By coupling the software with a tracking system and with the help of a special registration procedure, we are able to acquire dental occlusion plans from plaster model mounts. Upon completion of the surgical plan, the setup is used to manufacture positioning splints for intraoperative guidance. The system provides further intraoperative assistance with the help of a display showing jaw positions and 3-D positioning guides updated in real time during the surgical procedure. The proposed approach offers the advantages of 3-D visualization and tracking technology without sacrificing long-proven cast-based techniques for dental occlusion evaluation. The system has been applied on one patient. Throughout this procedure, we have experienced improved assessment of pathology, increased precision, and augmented control.

Non-photorealistic rendering of virtual implant models for computer-assisted fluoroscopy-based surgical procedures

Surgical navigation systems visualize the positions and orientations of surgical instruments and implants as graphical overlays onto a medical image of the operated anatomy on a computer monitor. The orthopaedic surgical navigation systems could be categorized according to the image modalities that are used for the visualization of surgical action. In the so-called CT-based systems or 'surgeon-defined anatomy' based systems, where a 3D volume or surface representation of the operated anatomy could be constructed from the preoperatively acquired tomographic data or through intraoperatively digitized anatomy landmarks, a photorealistic rendering of the surgical action has been identified to greatly improve usability of these navigation systems. However, this may not hold true when the virtual representation of surgical instruments and implants is superimposed onto 2D projection images in a fluoroscopy-based navigation system due to the so-called image occlusion problem. Image occlusion occurs when the field of view of the fluoroscopic image is occupied by the virtual representation of surgical implants or instruments. In these situations, the surgeon may miss part of the image details, even if transparency and/or wire-frame rendering is used. In this paper, we propose to use non-photorealistic rendering to overcome this difficulty. Laboratory testing results on foamed plastic bones during various computer-assisted fluoroscopybased surgical procedures including total hip arthroplasty and long bone fracture reduction and osteosynthesis are shown.

Noninvasive three-dimensional assessment of femoroacetabular impingement

A CT-based method ("HipMotion") for the noninvasive three-dimensional assessment of femoroacetabular impingement (FAI) was developed, validated, and applied in a clinical pilot study. The method allows for the anatomically based calculation of hip range of motion (ROM), the exact location of the impingement zone, and the simulation of quantified surgical maneuvers for FAI. The accuracy of HipMotion was 0.7 +/- 3.1 degrees in a plastic bone setup and -5.0 +/- 5.6 degrees in a cadaver setup. Reliability and reproducibility were excellent [intraclass correlation coefficient (ICC) > 0.87] for all measures except external rotation (ICC = 0.48). The normal ROM was determined from a cohort of 150 patients and was compared to 31 consecutive hips with FAI. Patients with FAI had a significantly decreased flexion, internal rotation, and abduction in comparison to normal hips (p < 0.001). Normal hip flexion and internal rotation are generally overestimated in a number of orthopedic textbooks. HipMotion is a useful tool for further assessment of impinging hips and for appropriate planning of the necessary amount of surgical intervention, which represents the basis for future computer-assisted treatment of FAI with less invasive surgical approaches, such as hip arthroscopy.

Definition, assessment and treatment of wheezing disorders in preschool children: an evidence-based approach

There is poor agreement on definitions of different phenotypes of preschool wheezing disorders. The present Task Force proposes to use the terms episodic (viral) wheeze to describe children who wheeze intermittently and are well between episodes, and multiple-trigger wheeze for children who wheeze both during and outside discrete episodes. Investigations are only needed when in doubt about the diagnosis. Based on the limited evidence available, inhaled short-acting beta(2)-agonists by metered-dose inhaler/spacer combination are recommended for symptomatic relief. Educating parents regarding causative factors and treatment is useful. Exposure to tobacco smoke should be avoided; allergen avoidance may be considered when sensitisation has been established. Maintenance treatment with inhaled corticosteroids is recommended for multiple-trigger wheeze; benefits are often small. Montelukast is recommended for the treatment of episodic (viral) wheeze and can be started when symptoms of a viral cold develop. Given the large overlap in phenotypes, and the fact that patients can move from one phenotype to another, inhaled corticosteroids and montelukast may be considered on a trial basis in almost any preschool child with recurrent wheeze, but should be discontinued if there is no clear clinical benefit. Large well-designed randomised controlled trials with clear descriptions of patients are needed to improve the present recommendations on the treatment of these common syndromes.

Probabilistic-based hurricane risk assessment and mitigation considering the potential impacts of climate change

Studies are suggesting that hurricane hazard patterns (e.g. intensity and frequency) may change as a consequence of the changing global climate. As hurricane patterns change, it can be expected that hurricane damage risks and costs may change as a result. This indicates the necessity to develop hurricane risk assessment models that are capable of accounting for changing hurricane hazard patterns, and develop hurricane mitigation and climatic adaptation strategies. This thesis proposes a comprehensive hurricane risk assessment and mitigation strategies that account for a changing global climate and that has the ability of being adapted to various types of infrastructure including residential buildings and power distribution poles. The framework includes hurricane wind field models, hurricane surge height models and hurricane vulnerability models to estimate damage risks due to hurricane wind speed, hurricane frequency, and hurricane-induced storm surge and accounts for the timedependant properties of these parameters as a result of climate change. The research then implements median insured house values, discount rates, housing inventory, etc. to estimate hurricane damage costs to residential construction. The framework was also adapted to timber distribution poles to assess the impacts climate change may have on timber distribution pole failure. This research finds that climate change may have a significant impact on the hurricane damage risks and damage costs of residential construction and timber distribution poles. In an effort to reduce damage costs, this research develops mitigation/adaptation strategies for residential construction and timber distribution poles. The costeffectiveness of these adaptation/mitigation strategies are evaluated through the use of a Life-Cycle Cost (LCC) analysis. In addition, a scenario-based analysis of mitigation strategies for timber distribution poles is included. For both residential construction and timber distribution poles, adaptation/mitigation measures were found to reduce damage costs. Finally, the research develops the Coastal Community Social Vulnerability Index (CCSVI) to include the social vulnerability of a region to hurricane hazards within this hurricane risk assessment. This index quantifies the social vulnerability of a region, by combining various social characteristics of a region with time-dependant parameters of hurricanes (i.e. hurricane wind and hurricane-induced storm surge). Climate change was found to have an impact on the CCSVI (i.e. climate change may have an impact on the social vulnerability of hurricane-prone regions).

Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.

Intravascular ultrasound-based left main coronary artery assessment: comparison between pullback from left anterior descending and circumflex arteries

We compared continuous pullback from the left anterior descending artery (LAD) with pullback from the circumflex artery (CX) for the assessment of the left main coronary artery (LMCA) by intravascular ultrasound (IVUS).

Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks

Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.