Evaluation of 3D gradient filters for estimation of the surface orientation in CTC

The extraction of the gradient information from 3D surfaces plays an important role for many applications including 3D graphics and medical imaging. The extraction of the 3D gradient information is performed by filtering the input data with high pass filters that are typically implemented using 3×3×3 masks. Since these filters extract the gradient information in small neighborhood, the estimated gradient information will be very sensitive to image noise. The development of a 3D gradient operator that is robust to image noise is particularly important since the medical datasets are characterized by a relatively low signal to noise ratio. The aim of this paper is to detail the implementation of an optimized 3D gradient operator that is applied to sample the local curvature of the colon wall in CT data and its influence on the overall performance of our CAD-CTC method. The developed 3D gradient operator has been applied to extract the local curvature of the colon wall in a large number CT datasets captured with different radiation doses and the experimental results are presented and discussed

The use of 3D surface fitting for robust polyp detection and classification in CT colonography

In this paper we describe the development of a computationally efficient computer-aided detection (CAD) algorithm based on the evaluation of the surface morphology that is employed for the detection of colonic polyps in computed tomography (CT) colonography. Initial polyp candidate voxels were detected using the surface normal intersection values. These candidate voxels were clustered using the normal direction, convexity test, region growing and Gaussian distribution. The local colonic surface was classified as polyp or fold using a feature normalized nearest neighborhood classifier. The main merit of this paper is the methodology applied to select the robust features derived from the colon surface that have a high discriminative power for polyp/fold classification. The devised polyp detection scheme entails a low computational overhead (typically takes 2.20 min per dataset) and shows 100% sensitivity for phantom polyps greater than 5 mm. It also shows 100% sensitivity for real polyps larger than 10 mm and 91.67% sensitivity for polyps between 5 to 10 mm with an average of 4.5 false positives per dataset. The experimental data indicates that the proposed CAD polyp detection scheme outperforms other techniques that identify the polyps using features that sample the colon surface curvature especially when applied to low-dose datasets

A fully automatic CAD-CTC system based on curvature analysis for standard and low-dose CT data

Computed tomography colonography (CTC) is a rapidly evolving noninvasive medical investigation that is viewed by radiologists as a potential screening technique for the detection of colorectal polyps. Due to the technical advances in CT system design, the volume of data required to be processed by radiologists has increased significantly, and as a consequence the manual analysis of this information has become an increasingly time consuming process whose results can be affected by inter- and intrauser variability. The aim of this paper is to detail the implementation of a fully integrated CAD-CTC system that is able to robustly identify the clinically significant polyps in the CT data. The CAD-CTC system described in this paper is a multistage implementation whose main system components are: 1) automatic colon segmentation; 2) candidate surface extraction; 3) feature extraction; and 4) classification. Our CAD-CTC system performs at 100% sensitivity for polyps larger than 10 mm, 92% sensitivity for polyps in the range 5 to 10 mm, and 57.14% sensitivity for polyps smaller than 5 mm with an average of 3.38 false positives per dataset. The developed system has been evaluated on synthetic and real patient CT data acquired with standard and low-dose radiation levels

Determining candidate polyp morphology from CT colonography using a level-set method

In this paper we propose a level-set segmentation for polyp candidates in Computer Tomography Colongraphy (CTC). Correct classification of the candidate polyps into polyp and non-polyp is, in most cases, evaluated using shape features. Therefore, accurate recovery of the polyp candidate surface is important for correct classification. The method presented in this paper, evolves a curvature and gradient dependent boundary to recover the surface of the polyp candidate in a level-set framework. The curvature term is computed using a combination of the Mean curvature and the Gaussian curvature. The results of the algorithm were run through a classifier for two complete data-sets and returned 100% sensitivity for polyps greater than 5mm

Exploring the effect of laser excitation wavelength on signal recovery with deep tissue transmission Raman spectroscopy.

PublishedJOURNAL ARTICLEThe aim of this research was to find the optimal Raman excitation wavelength to attain the largest possible sensitivity in deep Raman spectroscopy of breast tissue. This involved careful consideration of factors such as tissue absorption, scattering, fluorescence and instrument response function. The study examined the tissue absorption profile combined with Raman scattering and detection sensitivity at seven different, laser excitation wavelengths in the near infrared region of the spectrum. Several key scenarios in regards to the sample position within the tissue were examined. The highest Raman band visibility over the background ratio in respect to biological tissue provides the necessary information for determining the optimum laser excitation wavelength for deep tissue analysis using transmission Raman spectroscopy, including detection of breast calcifications. For thick tissues with a mix of protein and fat, such as breast tissue, 790-810 nm is concluded to be the optimum excitation wavelength for deep Raman measurements.An EPSRC grant (EP/K020374/1) funded the work presented here

Quantification of PLA Contamination in PET during Injection Moulding by In-line NIR Spectroscopy

PublishedArticleIn-line spectroscopy is a useful tool for monitoring processing conditions and polymer quality in the melt state in processes such as extrusion and injection moulding. This study extends the scope of this technique to the quantitative detection of poly(lactic acid) (PLA), which is a contaminant of concern in recycled poly(ethylene terephthalate) (PET). The near-infrared spectra of thermally treated PLA were studied for evidence of spectral changes which could be used as markers for PLA in PET, and these are discussed in detail. Several chemometric models for quantifying PLA in PET were developed and the influence of chemical or physical changes on the performance of the models is discussed. The selection of the final model was based on criteria aimed at eliminating interference due to spectral changes resulting from physical processes, to give a robust model based specifically on the chemistry of the polymers studied. Finally, the models were tested against a new test mixture of known composition and the outputs are discussed.This research was funded by Grant Agreement No. 285889 under the Seventh Framework Programme Theme SME-2011-2

Studies on the reprocessability of poly(ether ether ketone) (PEEK)

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Whilst demonstrating desirable mechanical properties, corrosion resistance and the ability to retain structural integrity over extended temperatures, PEEK (Poly (Ether Ether Ketone)) remains expensive, restricting broader usage. The reuse and recyclability characteristics of PEEK are therefore commercially important, where the most prevalent manufacturing process for PEEK is injection moulding. This study comments on the reprocessability of PEEK specifically applied to the injection moulding process, comparing the effect of repeated reuse on mechanical properties. Recycled PEEK retains its tensile properties through at least three moulding and regrinding cycles. XRD and DSC measurements confirmed that reused PEEK shows no degradation in crystallinity.The authors would like to thank Dave Baker for technical support and Rachel Trimble for comments on the manuscript. This work was part of a project co-funded by the Technology Strategy Board’s (TSB) Collaborative Research and Development programme, following an open competition

Sensitivity of Transmission Raman Spectroscopy Signals to Temperature of Biological Tissues

This is the final version of the article. Available from Springer Nature via the DOI in this record.Optical properties of biological tissues can be influenced by their temperature, thus affecting light transport inside the sample. This could potentially be exploited to deliver more photons inside large biological samples, when compared with experiments at room temperature, overcoming some of difficulties due to highly scattering nature of the tissue. Here we report a change in light transmitted inside biological tissue with temperature elevation from 20 to 40 °C, indicating a considerable enhancement of photons collected by the detector in transmission geometry. The measurement of Raman signals in porcine tissue samples, as large as 40 mm in thickness, indicates a considerable increase in signal ranging from 1.3 to 2 fold, subject to biological variability. The enhancements observed are ascribed to phase transitions of lipids in biological samples. This indicates that: 1) experiments performed on tissue at room temperature can lead to an underestimation of signals that would be obtained at depth in the body in vivo and 2) that experiments at room temperature could be modified to increase detection limits by elevating the temperature of the material of interest.The work was supported by a grant from the Engineering and Physical research council (EP/P012442/1)

A Unified Forensics Analysis Approach to Digital Investigation

Digital forensics is now essential in addressing cybercrime and cyber-enabled crime but potentially it can have a role in almost every other type of crime. Given technology's continuous development and prevalence, the widespread adoption of technologies among society and the subsequent digital footprints that exist, the analysis of these technologies can help support investigations. The abundance of interconnected technologies and telecommunication platforms has significantly changed the nature of digital evidence. Subsequently, the nature and characteristics of digital forensic cases involve an enormous volume of data heterogeneity, scattered across multiple evidence sources, technologies, applications, and services. It is indisputable that the outspread and connections between existing technologies have raised the need to integrate, harmonise, unify and correlate evidence across data sources in an automated fashion. Unfortunately, the current state of the art in digital forensics leads to siloed approaches focussed upon specific technologies or support of a particular part of digital investigation. Due to this shortcoming, the digital investigator examines each data source independently, trawls through interconnected data across various sources, and often has to conduct data correlation manually, thus restricting the digital investigator’s ability to answer high-level questions in a timely manner with a low cognitive load. Therefore, this research paper investigates the limitations of the current state of the art in the digital forensics discipline and categorises common investigation crimes with the necessary corresponding digital analyses to define the characteristics of the next-generation approach. Based on these observations, it discusses the future capabilities of the next-generation unified forensics analysis tool (U-FAT), with a workflow example that illustrates data unification, correlation and visualisation processes within the proposed method.</jats:p

Pengaruh Budaya Organisasi dan Persepsi Dukungan Organisasi terhadap Komitmen Karyawan

The purpose of this study is to investigate the influence of organizational culture and perceived organizational support toward organizational commitment. The instrument was used in this study were organizational commitment scale is based on aspects of organizational commitment, organizational culture scale is based on aspects of organizational culture and perceived organizational support scale based on aspects of the perceived organizational support. This study was involved 203 banking employees. The results showed that organizational culture and perceived organizational support significantly influenced of organizational commitment. It means organizational culture and perceived organizational support contributed to increasing organizational commitment. Meanwhile, organizational culture has a greater contribution to organizational commitment than perceived organizational support. This study also showed that two aspects of organizational culture contributed to organizational commitment, there were espoused values and artifacts. An espoused value has a higher contributed to organizational commitment. Meanwhile, for perceived organizational support, fairness aspect contributed to organizational commitment