Hash based disk imaging using AFF4

Forensic imaging has been facing scalability challenges for some time. As disk capacity growth continues to outpace storage IO bandwidth, the demands placed on storage and time are ever increasing. Data reduction and de-duplication technologies are now commonplace in the Enterprise space, and are potentially applicable to forensic acquisition. Using the new AFF4 forensic file format we employ a hash based compression scheme to leverage an existing corpus of images, reducing both acquisition time and storage requirements. This paper additionally describes some of the recent evolution in the AFF4 file format making the efficient implementation of hash based imaging a reality.

Contrast enhancement of EPID images via difference imaging : a feasibility study

In this study, the feasibility of difference imaging for improving the contrast of electronic portal imaging device (EPID) images is investigated. The difference imaging technique consists of the acquisition of two EPID images (with and without the placement of an additional layer of attenuating medium on the surface of the EPID)and the subtraction of one of these images from the other. The resulting difference image shows improved contrast, compared to a standard EPID image, since it is generated by lower-energy photons. Results of this study show that, ¯rstly, this method can produce images exhibiting greater contrast than is seen in standard megavoltage EPID images and that, secondly, the optimal thickness of attenuating material for producing a maximum contrast enhancement may vary with phantom thickness and composition. Further studies of the possibilities and limitations of the di®erence imaging technique, and the physics behind it, are therefore recommended.

A research opportunity : “3D-ROSE” : virtual reality preparation for children having radiotherapy or imaging procedures

Professor Christian Langton is a medical physicist at Queensland University of Technology in Brisbane. He has developed a way of preparing children who are about to have either radiotherapy or MRI imaging procedures and is seeking research partners to develop and test these further. This is a great opportunity for nurses interested in research, and who have access to a children’s hospital, to work with Professor Langton on some truly innovative, multidisciplinary research.

Formalin fixation affects equilibrium partitioning of an ionic contrast agent-microcomputed tomography (EPIC-[mu]CT) imaging of osteochondral samples

Equilibrium Partitioning of an Ionic Contrast agent with microcomputed tomography (EPIC-[mu]CT) is a non-invasive technique to quantify and visualize the three-dimensional distribution of glycosaminoglycans (GAGs) in fresh cartilage tissue. However, it is unclear whether this technique is applicable to already fixed tissues. Therefore, this study aimed at investigating whether formalin fixation of bovine cartilage affects X-ray attenuation, and thus the interpretation of EPIC-[mu]CT data.Design Osteochondral samples (n = 24) were incubated with ioxaglate, an ionic contrast agent, for 22 h prior to [mu]CT scanning. The samples were scanned in both formalin-fixed and fresh conditions. GAG content was measured using a biochemical assay and normalized to wet weight, dry weight, and water content to determine potential reasons for differences in X-ray attenuation.Results The expected zonal distribution of contrast agent/GAGs was observed for both fixed and fresh cartilage specimens. However, despite no significant differences in GAG concentrations or physical properties between fixed and fresh samples, the average attenuation levels of formalin-fixed cartilage were 14.3% lower than in fresh samples.Conclusions EPIC-[mu]CT is useful for three-dimensional visualization of GAGs in formalin-fixed cartilage. However, a significant reduction in X-ray attenuation for fixed (compared to fresh) cartilage must be taken into account and adjusted for accordingly when quantifying GAG concentrations using EPIC-[mu]CT.

A crash avoidance framework for heavy equipment control systems using 3D imaging sensors

This paper presents a preliminary crash avoidance framework for heavy equipment control systems. Safe equipment operation is a major concern on construction sites since fatal on-site injuries are an industry-wide problem. The proposed framework has potential for effecting active safety for equipment operation. The framework contains algorithms for spatial modeling, object tracking, and path planning. Beyond generating spatial models in fractions of seconds, these algorithms can successfully track objects in an environment and produce a collision-free 3D motion trajectory for equipment.

Laser doppler imaging in a paediatric burns population

Objective Laser Doppler imaging (LDI) was compared to wound outcomes in children's burns, to determine if the technology could be used to predict these outcomes. Methods Forty-eight patients with a total of 85 burns were included in the study. Patient median age was 4 years 10 months and scans were taken 0–186 h post-burn using the fast, low-resolution setting on the Moor LDI2 laser Doppler imager. Wounds were managed by standard practice, without taking into account the scan results. Time until complete re-epithelialisation and whether or not grafting and scar management were required were recorded for each wound. If wounds were treated with Silvazine™ or Acticoat™ prior to the scan, this was also recorded. Results The predominant colour of the scan was found to be significantly related to the re-epithelialisation, grafting and scar management outcomes and could be used to predict those outcomes. The prior use of Acticoat™ did not affect the scan relationship to outcomes, however, the use of Silvazine™ did complicate the relationship for light blue and green scanned partial thickness wounds. Scans taken within the 24-h window after-burn also appeared to be accurate predictors of wound outcome. Conclusion Laser Doppler imaging is accurate and effective in a paediatric population with a low-resolution fast-scan.

Bayesian methodology for genetics of complex diseases

Genetic research of complex diseases is a challenging, but exciting, area of research. The early development of the research was limited, however, until the completion of the Human Genome and HapMap projects, along with the reduction in the cost of genotyping, which paves the way for understanding the genetic composition of complex diseases. In this thesis, we focus on the statistical methods for two aspects of genetic research: phenotype definition for diseases with complex etiology and methods for identifying potentially associated Single Nucleotide Polymorphisms (SNPs) and SNP-SNP interactions. With regard to phenotype definition for diseases with complex etiology, we firstly investigated the effects of different statistical phenotyping approaches on the subsequent analysis. In light of the findings, and the difficulties in validating the estimated phenotype, we proposed two different methods for reconciling phenotypes of different models using Bayesian model averaging as a coherent mechanism for accounting for model uncertainty. In the second part of the thesis, the focus is turned to the methods for identifying associated SNPs and SNP interactions. We review the use of Bayesian logistic regression with variable selection for SNP identification and extended the model for detecting the interaction effects for population based case-control studies. In this part of study, we also develop a machine learning algorithm to cope with the large scale data analysis, namely modified Logic Regression with Genetic Program (MLR-GEP), which is then compared with the Bayesian model, Random Forests and other variants of logic regression.

Improved image quality for x-ray CT imaging of gel dosimeters

Purpose: This study provides a simple method for improving precision of x-ray computed tomography (CT) scans of irradiated polymer gel dosimetry. The noise affecting CT scans of irradiated gels has been an impediment to the use of clinical CT scanners for gel dosimetry studies. Method: In this study, it is shown that multiple scans of a single PAGAT gel dosimeter can be used to extrapolate a ‘zero-scan’ image which displays a similar level of precision to an image obtained by averaging multiple CT images, without the compromised dose measurement resulting from the exposure of the gel to radiation from the CT scanner. Results: When extrapolating the zero-scan image, it is shown that exponential and simple linear fits to the relationship between Hounsfield unit and scan number, for each pixel in the image, provides an accurate indication of gel density. Conclusions: It is expected that this work will be utilised in the analysis of three-dimensional gel volumes irradiated using complex radiotherapy treatments.