Development and implementation of a web-enabled 3D consultation tool for breast augmentation surgery based on 3D-image reconstruction of 2D pictures

Producing a rich, personalized Web-based consultation tool for plastic surgeons and patients is challenging.

Content comparison of health status measures for obesity based on the international classification of functioning, disability and health

OBJECTIVE: To compare the content covered by twelve obesity-specific health status measures using the International Classification of Functioning, Disability and Health (ICF). DESIGN: Obesity-specific health status measures were identified and then linked to the ICF separately by two trained health professionals according to standardized guidelines. The degree of agreement between health professionals was calculated by means of the kappa (kappa) statistic. Bootstrapped confidence intervals (CI) were calculated. The obesity-specific health-status measures were compared on the component and category level of the ICF. MEASUREMENTS: welve condition-specific health-status measures were identified and included in this study, namely the obesity-related problem scale, the obesity eating problems scale, the obesity-related coping and obesity-related distress questionnaire, the impact of weight on quality of life questionnaire (short version), the health-related quality of life questionnaire, the obesity adjustment survey (short form), the short specific quality of life scale, the obesity-related well-being questionnaire, the bariatric analysis and reporting outcome system, the bariatric quality of life index, the obesity and weight loss quality of life questionnaire and the weight-related symptom measure. RESULTS: In the 280 items of the eight measures, a total of 413 concepts were identified and linked to the 87 different ICF categories. The measures varied strongly in the number of concepts contained and the number of ICF categories used to map these concepts. Items on body functions varied form 12% in the obesity-related problem scale to 95% in the weight-related symptom measure. The estimated kappa coefficients ranged between 0.79 (CI: 0.72, 0.86) at the component ICFs level and 0.97 (CI: 0.93, 1.0) at the third ICF's level. CONCLUSION: The ICF proved highly useful for the content comparison of obesity-specific health-status measures. The results may provide clinicians and researchers with new insights when selecting health-status measures for clinical studies in obesity.

Assessment of spline-based 2D-3D registration for image-guided spine surgery

2D-3D registration of pre-operative 3D volumetric data with a series of calibrated and undistorted intra-operative 2D projection images has shown great potential in CT-based surgical navigation because it obviates the invasive procedure of the conventional registration methods. In this study, a recently introduced spline-based multi-resolution 2D-3D image registration algorithm has been adapted together with a novel least-squares normalized pattern intensity (LSNPI) similarity measure for image guided minimally invasive spine surgery. A phantom and a cadaver together with their respective ground truths were specially designed to experimentally assess possible factors that may affect the robustness, accuracy, or efficiency of the registration. Our experiments have shown that it is feasible for the assessed 2D-3D registration algorithm to achieve sub-millimeter accuracy in a realistic setup in less than one minute.

Projector-based augmented reality for intuitive intraoperative guidance in image-guided 3D interstitial brachytherapy

PURPOSE: The aim of this study is to implement augmented reality in real-time image-guided interstitial brachytherapy to allow an intuitive real-time intraoperative orientation. METHODS AND MATERIALS: The developed system consists of a common video projector, two high-resolution charge coupled device cameras, and an off-the-shelf notebook. The projector was used as a scanning device by projecting coded-light patterns to register the patient and superimpose the operating field with planning data and additional information in arbitrary colors. Subsequent movements of the nonfixed patient were detected by means of stereoscopically tracking passive markers attached to the patient. RESULTS: In a first clinical study, we evaluated the whole process chain from image acquisition to data projection and determined overall accuracy with 10 patients undergoing implantation. The described method enabled the surgeon to visualize planning data on top of any preoperatively segmented and triangulated surface (skin) with direct line of sight during the operation. Furthermore, the tracking system allowed dynamic adjustment of the data to the patient's current position and therefore eliminated the need for rigid fixation. Because of soft-part displacement, we obtained an average deviation of 1.1 mm by moving the patient, whereas changing the projector's position resulted in an average deviation of 0.9 mm. Mean deviation of all needles of an implant was 1.4 mm (range, 0.3-2.7 mm). CONCLUSIONS: The developed low-cost augmented-reality system proved to be accurate and feasible in interstitial brachytherapy. The system meets clinical demands and enables intuitive real-time intraoperative orientation and monitoring of needle implantation.

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.

Validation of water vapour profiles (version 13) retrieved by the IMK / IAA scientific retrieval processor based on full resolution spectra measured by MIPAS on board Envisat

Vertical profiles of stratospheric water vapour measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) with the full resolution mode between September 2002 and March 2004 and retrieved with the IMK/IAA scientific retrieval processor were compared to a number of independent measurements in order to estimate the bias and to validate the existing precision estimates of the MIPAS data. The estimated precision for MIPAS is 5 to 10% in the stratosphere, depending on altitude, latitude, and season. The independent instruments were: the Halogen Occultation Experiment (HALOE), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the Improved Limb Atmospheric Spectrometer-II (ILAS-II), the Polar Ozone and Aerosol Measurement (POAM III) instrument, the Middle Atmospheric Water Vapour Radiometer (MIAWARA), the Michelson Interferometer for Passive Atmospheric Sounding, balloon-borne version (MIPAS-B), the Airborne Microwave Stratospheric Observing System (AMSOS), the Fluorescent Stratospheric Hygrometer for Balloon (FLASH-B), the NOAA frostpoint hygrometer, and the Fast In Situ Hygrometer (FISH). For the in-situ measurements and the ground based, air- and balloon borne remote sensing instruments, the measurements are restricted to central and northern Europe. The comparisons to satellite-borne instruments are predominantly at mid- to high latitudes on both hemispheres. In the stratosphere there is no clear indication of a bias in MIPAS data, because the independent measurements in some cases are drier and in some cases are moister than the MIPAS measurements. Compared to the infrared measurements of MIPAS, measurements in the ultraviolet and visible have a tendency to be high, whereas microwave measurements have a tendency to be low. The results of χ2-based precision validation are somewhat controversial among the comparison estimates. However, for comparison instruments whose error budget also includes errors due to uncertainties in spectrally interfering species and where good coincidences were found, the χ2 values found are in the expected range or even below. This suggests that there is no evidence of systematically underestimated MIPAS random errors.

Adjuvant therapy after resection of brain metastases. Frameless image-guided LINAC-based radiosurgery and stereotactic hypofractionated radiotherapy

BACKGROUND: Tumor bed stereotactic radiosurgery (SRS) after resection of brain metastases is a new strategy to delay or avoid whole-brain irradiation (WBRT) and its associated toxicities. This retrospective study analyzes results of frameless image-guided linear accelerator (LINAC)-based SRS and stereotactic hypofractionated radiotherapy (SHRT) as adjuvant treatment without WBRT. MATERIALS AND METHODS: Between March 2009 and February 2012, 44 resection cavities in 42 patients were treated with SRS (23 cavities) or SHRT (21 cavities). All treatments were delivered using a stereotactic LINAC. All cavities were expanded by ≥ 2 mm in all directions to create the clinical target volume (CTV). RESULTS: The median planning target volume (PTV) for SRS was 11.1 cm(3). The median dose prescribed to the PTV margin for SRS was 17 Gy. Median PTV for SHRT was 22.3 cm(3). The fractionation schemes applied were: 4 fractions of 6 Gy (5 patients), 6 fractions of 4 Gy (6 patients) and 10 fractions of 4 Gy (10 patients). Median follow-up was 9.6 months. Local control (LC) rates after 6 and 12 months were 91 and 77 %, respectively. No statistically significant differences in LC rates between SRS and SHRT treatments were observed. Distant brain control (DBC) rates at 6 and 12 months were 61 and 33 %, respectively. Overall survival (OS) at 6 and 12 months was 87 and 63.5 %, respectively, with a median OS of 15.9 months. One patient treated by SRS showed symptoms of radionecrosis, which was confirmed histologically. CONCLUSION: Frameless image-guided LINAC-based adjuvant SRS and SHRT are effective and well tolerated local treatment strategies after resection of brain metastases in patients with oligometastatic disease.

Informative State-Based Video Communication

We study state-based video communication where a client simultaneously informs the server about the presence status of various packets in its buffer. In sender-driven transmission, the client periodically sends to the server a single acknowledgement packet that provides information about all packets that have arrived at the client by the time the acknowledgment is sent. In receiver-driven streaming, the client periodically sends to the server a single request packet that comprises a transmission schedule for sending missing data to the client over a horizon of time. We develop a comprehensive optimization framework that enables computing packet transmission decisions that maximize the end-to-end video quality for the given bandwidth resources, in both prospective scenarios. The core step of the optimization comprises computing the probability that a single packet will be communicated in error as a function of the expected transmission redundancy (or cost) used to communicate the packet. Through comprehensive simulation experiments, we carefully examine the performance advances that our framework enables relative to state-of-the-art scheduling systems that employ regular acknowledgement or request packets. Consistent gains in video quality of up to 2B are demonstrated across a variety of content types. We show that there is a direct analogy between the error-cost efficiency of streaming a single packet and the overall rate-distortion performance of streaming the whole content. In the case of sender-driven transmission, we develop an effective modeling approach that accurately characterizes the end-to-end performance as a function of the packet loss rate on the backward channel and the source encoding characteristics.

A Food Recognition System for Diabetic Patients based on an Optimized Bag of Features Model

Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5,000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10,000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

An image-based method to automatically propagate bony landmarks: application to computational spine biomechanics.

In attempts to elucidate the underlying mechanisms of spinal injuries and spinal deformities, several experimental and numerical studies have been conducted to understand the biomechanical behavior of the spine. However, numerical biomechanical studies suffer from uncertainties associated with hard- and soft-tissue anatomies. Currently, these parameters are identified manually on each mesh model prior to simulations. The determination of soft connective tissues on finite element meshes can be a tedious procedure, which limits the number of models used in the numerical studies to a few instances. In order to address these limitations, an image-based method for automatic morphing of soft connective tissues has been proposed. Results showed that the proposed method is capable to accurately determine the spatial locations of predetermined bony landmarks. The present method can be used to automatically generate patient-specific models, which may be helpful in designing studies involving a large number of instances and to understand the mechanical behavior of biomechanical structures across a given population.

Image-based vs. mesh-based statistical appearance models of the human femur: Implications for finite element simulations.

Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.