Elastic Registration of Biological Images Using Vector-Spline Regularization

We present an elastic registration algorithm for the alignment of biological images. Our method combines and extends some of the best techniques available in the context of medical imaging. We express the deformation field as a B-spline model, which allows us to deal with a rich variety of deformations. We solve the registration problem by minimizing a pixelwise mean-square distance measure between the target image and the warped source. The problem is further constrained by way of a vector-spline regularization which provides some control over two independent quantities that are intrinsic to the deformation: its divergence, and its curl. Our algorithm is also able to handle soft landmark constraints, which is particularly useful when parts of the images contain very little information or when its repartition is uneven. We provide an optimal analytical solution in the case when only landmarks and smoothness considerations are taken into account. We have applied our approach to perform the elastic registration of images such as electrophoretic gels and fly embryos. The validation of the results by experts has been favorable in all cases

Computational Methods on Study of Differentially Expressed Proteins in Maize Proteomes Associated with Resistance to Aflatoxin Accumulation

Plant breeders have focused on improving maize resistance to Aspergillus flavus infection and aflatoxin accumulation by breeding with genotypes having the desirable traits. Various maize inbred lines have been developed for the breeding of resistance. Identification of differentially expressed proteins among such maize inbred lines will facilitate the development of gene markers and expedite the breeding process. Computational biology and proteomics approaches on the investigation of differentially expressed proteins were explored in this research. The major research objectives included 1) application of computational methods in homology and comparative modeling to study 3D protein structures and identify single nucleotide polymorphisms (SNPs) involved in changes of protein structures and functions, which can in turn increase the efficiency of the development of DNA markers; 2) investigation of methods on total protein profiling including purification, separation, visualization, and computational analysis at the proteome level. Special research goals were set on the development of open source computational methods using Matlab image processing tools to quantify and compare protein expression levels visualized by 2D protein electrophoresis gel techniques

Registration and 3D reconstruction of histological sections: application to mammary gland development

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, mayo de 200

Characterising pattern asymmetry in pigmented skin lesions

Abstract. In clinical diagnosis of pigmented skin lesions asymmetric pigmentation is often indicative of melanoma. This paper describes a method and measures for characterizing lesion symmetry. The estimate of mirror symmetry is computed first for a number of axes at different degrees of rotation with respect to the lesion centre. The statistics of these estimates are the used to assess the overall symmetry. The method is applied to three different lesion representations showing the overall pigmentation, the pigmentation pattern, and the pattern of dermal melanin. The best measure is a 100% sensitive and 96% specific indicator of melanoma on a test set of 33 lesions, with a separate training set consisting of 66 lesions

Image Registration Workshop Proceedings

Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research

Modelling and verification of doses delivered to deformable moving targets in radiotherapy

During the last two decades, advanced treatment techniques have been developed in radiotherapy to achieve more conformal beam targeting of cancerous lesions. The advent of these techniques, such as intensity modulated radiotherapy (IMRT), volumetric modulated arc radiothreapy (VMAT), Tomotherapy etc., allows more precise localisation of higher doses to complex-shaped target volumes, thereby sparing more healthy tissue. In this context, motion management is a critical issue in contemporary radiotherapy (RT). That anatomic structures move during respiration is well known and much research is presently being devoted to strategies to contend with organ motion. However, moving structures are typically regarded as rigid bodies. The fact that many structures deform as a result of motion makes their resultant dose distributions difficult to measure and calculate, and has not been fully accounted for. The potential for ineffective treatments that do not take into account motion and anatomic deformation is self-evident. This thesis addresses the pressing need to investigate dose distributions in targets that deform during and/or between treatments, to ensure robust calculations for dose accumulation and delivery, thus providing the most positive outcomes for patients. This involves the direct measurement of complex and re-distributed dose in deforming objects (an experimental model), as well as calculations of the deformed dose distribution (a mathematical model). The comparison thereof aims to validate the dose deformation technique, thereby to apply the method to a clinical example such as liver stereotactic body radiotherapy. To facilitate four-dimensional deformable dosimetry for both external beam radiotherapy and brachytherapy, methodologies for three-dimensional deformed dose measurements were developed and employed using radiosensitive polymer gel combined with a cone beam optical computed tomography (CT) scanner. This includes the development of a novel prototype deformable target volume using a tissue-equivalent, deformable gel dosimetric phantom, dubbed “defgel”. This can reproducibly simulate targets subject to a range of mass- and density-conserving deformations representative of those observable in anatomical targets. This novel tool was characterised in terms of its suitability for the measurement of dose in deforming geometries. It was demonstrated that planned doses could be delivered to the deformable gel dosimeter in the presence of different deformations and complex spatial re-distributions of dose in all three dimensions could be quantified. For estimating the cumulative dose in different deformed states, deformable image registration (DIR) algorithms were implemented to ‘morph’ a dose distribution calculated by a treatment planning system. To investigate the performance of DIR and dose-warping technique, two key studies were undertaken. The first was to systematically assess the accuracy of a range of different DIR algorithms available in the public domain and quantitatively examine, in particular, low-contrast regions, where accuracy had not previously been established. This work investigates DIR algorithms in 3D via a systematic evaluation process using defgel suitable for verification of mass- and density-conserving deformations. The second study was a full three-dimensional experimental validation of the dose-warping technique using the evaluated DIR algorithm and comparing it to directly measured deformed dose distributions from defgel. It was shown that the dose-warping can be accurate, i.e. over 95% passing rate of 3D-gamma analysis with 3%/3mm criteria for given extents of deformation up to 20 mm For the application of evaluating patient treatment planning involving tumour motion/deformation, two key studies were undertaken in the context of liver stereotactic body radiotherapy. The first was a 4D evaluation of conventional 3D treatment planning, combined with 4D computed tomography, in order to investigate the extent of dosimetric differences between conventional 3D-static and path-integrated 4D-cumulative dose calculation. This study showed that the 3D planning approach overestimated doses to targets by ≤ 9% and underestimated dose to normal liver by ≤ 8%, compared to the 4D methodology. The second study was to assess a consequent reduction of healthy tissue sparing, which may increase risk for surrounding healthy tissues. Estimates for normal tissue complications probabilities (NTCP) based on the two dose calculation schemes are provided. While all NTCP were low for the employed fractionation scheme, analysis of common alternative schemes suggests potentially larger uncertainties exist in the estimation of NTCP for healthy liver and that substantial differences in these values may exist across the different fractionation schemes. These bodies of work have shown the potential to quantify such issues of under- and/or over-dosages which are quite patient dependent in RT. Studies presented in this work consolidate gel dosimetry, image guidance, DIR, dose-warping and consequent dose accumulation calculation to investigate the dosimetric impact and make more accurate evaluation of conventional 3D treatment plans. While liver stereotactic body radiotherapy (SBRT) was primarily concerned for immediate clinical application, the findings of this thesis are also applicable to other organs with various RT techniques. Most importantly, however, it is hoped that the outcomes of this thesis will help to improve treatment plan accuracy. By considering both computation and measurement, it is also hoped that this work will open new windows for future work and hence provide building blocks to further enhance the benefit of radiotherapy treatment

Anthropometric and genetic determinants of cardiac morphology and function

Background Cardiac structure and function result from complex interactions between genetic and environmental factors. Population-based studies have relied on 2-dimensional cardiovascular magnetic resonance as the gold-standard for phenotyping. However, this technique provides limited global metrics and is insensitive to regional or asymmetric changes in left ventricular (LV) morphology. High-resolution 3-dimensional cardiac magnetic resonance (3D-CMR) with computational quantitative phenotyping, might improve on traditional CMR by enabling the creation of detailed 3D statistical models of the variation in cardiac phenotypes for use in studies of genetic and/or environmental effects on cardiac form or function. Purpose To determine whether 3D-CMR is applicable at scale, and provides methodological and statistical advantages over conventional imaging for large-scale population studies and to apply 3D-CMR to anthropometric and genetic studies of the heart. Methods 1530 volunteers (54.8% females, 74.7% Caucasian, mean age 41.3±13.0 years) without self-reported cardiovascular disease were recruited prospectively to the Digital Heart Project. Using a cardiac atlas-based software, these images were computationally processed and quantitatively analysed. Parameters such as myocardial shape, curvature, wall thickness, relative wall thickness, end-systolic wall stress, fractional wall thickening and ventricular volumes were extracted at over 46,000 points in the model. The relationships between these parameters and systolic blood pressure (SBP), fat mass, lean mass and genetic variationswere analysed using 3D regression models adjusted for body surface area, gender, race, age and multiple testing. Targeted resequencing of titin (TTN), the largest human gene and the commonest genetic cause of dilated cardiomyopathy, was performed in 928 subjects while common variants (~700.000) were genotyped in 1346 subjects. Results Automatically segmented 3D images were more accurate than 2D images at defining cardiac surfaces, resulting in fewer subjects being required to detect a statistically significant 1 mm difference in wall thickness. 3D-CMR enabled the detection of a strong and distinct regionality of the effects of SBP, body composition and genetic variation on the heart. It shows that the precursors of the hypertensive heart phenotype can be traced to healthy normotensives and that different ratios of body composition are associated with particular gender-specific patterns of cardiac remodelling. In 17 asymptomatic subjects with genetic variations associated with dilated cardiomyopathy, early stages of ventricular impairment and wall thinning were identified, which were not apparent by 2D imaging. Conclusions 3D-CMR combined with computational modelling provides high-resolution insight into the earliest stages of heart disease. These methods show promise for population-based studies of the anthropometric, environmental and genetic determinants of LV form and function in health and disease.Open Acces