Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

The sideways hourglass : establishing the lemniscate as a narrative structure for writing and reading non-linear stories

This thesis is a study in narratology that examines the pre-theoretical ideas that underlie the study of narrative and time. The thesis explores how the lemniscate can be transported from geometry to narrative in order to structure a non-linear story that breaks the rules of causality and chronology by coupling physical movement through space with the backward pull of memory. The findings offer new possibilities for understanding the nexus between shape and story and for recording non-linear narratives that are marked by simultaneity, counterpoint, and reversal.

Reading words into statutes : when Homer nods

The grammatical meaning of a statutory provision may not always gel with the purpose of the statute. The court may strive to give the provision an interpretation at odds with its ordinary and natural meaning to meet the purpose of the legislation. On occasion, this may involve notionally adding words to, or substituting words in, a statutory provision. This process of “reading in” words demands that close attention be paid to the boundary between statutory construction and judicial legislation, particularly where a court is invited to carve out an exception from grammatically clear words. In Jones v Wrotham Park Settled Estates [1980] AC 74, Lord Diplock identified three pre-conditions to reading words into a statute. This article analyses the utility of those conditions within the context of the modern purposive approach to statutory interpretation and evaluates whether they remain sufficient guideposts for identifying the boundary between interpretation and legislation.

Perception of prescription medicine sample packs among Australian professional, government, industry, and consumer organizations, based on automated textual analysis of one-on-one interviews

Background Prescription medicine samples provided by pharmaceutical companies are predominantly newer and more expensive products. The range of samples provided to practices may not represent the drugs that the doctors desire to have available. Few studies have used a qualitative design to explore the reasons behind sample use. Objective The aim of this study was to explore the opinions of a variety of Australian key informants about prescription medicine samples, using a qualitative methodology. Methods Twenty-three organizations involved in quality use of medicines in Australia were identified, based on the authors' previous knowledge. Each organization was invited to nominate 1 or 2 representatives to participate in semistructured interviews utilizing seeding questions. Each interview was recorded and transcribed verbatim. Leximancer v2.25 text analysis software (Leximancer Pty Ltd., Jindalee, Queensland, Australia) was used for textual analysis. The top 10 concepts from each analysis group were interrogated back to the original transcript text to determine the main emergent opinions. Results A total of 18 key interviewees representing 16 organizations participated. Samples, patient, doctor, and medicines were the major concepts among general opinions about samples. The concept drug became more frequent and the concept companies appeared when marketing issues were discussed. The Australian Pharmaceutical Benefits Scheme and cost were more prevalent in discussions about alternative sample distribution models, indicating interviewees were cognizant of budgetary implications. Key interviewee opinions added richness to the single-word concepts extracted by Leximancer. Conclusions Participants recognized that prescription medicine samples have an influence on quality use of medicines and play a role in the marketing of medicines. They also believed that alternative distribution systems for samples could provide benefits. The cost of a noncommercial system for distributing samples or starter packs was a concern. These data will be used to design further research investigating alternative models for distribution of samples.

Automated power semiconductor switching performance feature extraction from experimental double-pulse waveform data

Double-pulse tests are commonly used as a method for assessing the switching performance of power semiconductor switches in a clamped inductive switching application. Data generated from these tests are typically in the form of sampled waveform data captured using an oscilloscope. In cases where it is of interest to explore a multi-dimensional parameter space and corresponding result space it is necessary to reduce the data into key performance metrics via feature extraction. This paper presents techniques for the extraction of switching performance metrics from sampled double-pulse waveform data. The reported techniques are applied to experimental data from characterisation of a cascode gate drive circuit applied to power MOSFETs.

Simulated hyperopic anisometropia and reading, visual information processing, and reading-related eye movement performance in children

Purpose: This study investigated the impact of simulated hyperopic anisometropia and sustained near work on performance of academic-related measures in children. Methods: Participants included 16 children (mean age: 11.1 ± 0.8 years) with minimal refractive error. Academic-related outcome measures included a reading test (Neale Analysis of Reading Ability), visual information processing tests (Coding and Symbol Search subtests from the Wechsler Intelligence Scale for Children) and a reading-related eye movement test (Developmental Eye Movement test). Performance was assessed with and without 0.75 D of imposed monocular hyperopic defocus (administered in a randomised order), before and after 20 minutes of sustained near work. Unilateral hyperopic defocus was systematically assigned to either the dominant or non-dominant sighting eye to evaluate the impact of ocular dominance on any performance decrements. Results: Simulated hyperopic anisometropia and sustained near work both independently reduced performance on all of the outcome measures (p<0.001). A significant interaction was also observed between simulated anisometropia and near work (p<0.05), with the greatest decrement in performance observed during simulated anisometropia in combination with sustained near work. Laterality of the refractive error simulation (ocular dominance) did not significantly influence the outcome measures (p>0.05). A reduction of up to 12% in performance was observed across the range of academic-related measures following sustained near work undertaken during the anisometropic simulation. Conclusion: Simulated hyperopic anisometropia significantly impaired academic–related performance, particularly in combination with sustained near work. The impact of uncorrected habitual anisometropia on academic-related performance in children requires further investigation.

Fully automated, semiautomated, and manual morphometric analysis of corneal subbasal nerve plexus in individuals with and without diabetes

Purpose The aim of the study was to determine the association, agreement, and detection capability of manual, semiautomated, and fully automated methods of corneal nerve fiber length (CNFL) quantification of the human corneal subbasal nerve plexus (SNP). Methods Thirty-three participants with diabetes and 17 healthy controls underwent laser scanning corneal confocal microscopy. Eight central images of the SNP were selected for each participant and analyzed using manual (CCMetrics), semiautomated (NeuronJ), and fully automated (ACCMetrics) software to quantify the CNFL. Results For the entire cohort, mean CNFL values quantified by CCMetrics, NeuronJ, and ACCMetrics were 17.4 ± 4.3 mm/mm2, 16.0 ± 3.9 mm/mm2, and 16.5 ± 3.6 mm/mm2, respectively (P < 0.01). CNFL quantified using CCMetrics was significantly higher than those obtained by NeuronJ and ACCMetrics (P < 0.05). The 3 methods were highly correlated (correlation coefficients 0.87–0.98, P < 0.01). The intraclass correlation coefficients were 0.87 for ACCMetrics versus NeuronJ and 0.86 for ACCMetrics versus CCMetrics. Bland–Altman plots showed good agreement between the manual, semiautomated, and fully automated analyses of CNFL. A small underestimation of CNFL was observed using ACCMetrics with increasing the amount of nerve tissue. All 3 methods were able to detect CNFL depletion in diabetic participants (P < 0.05) and in those with peripheral neuropathy as defined by the Toronto criteria, compared with healthy controls (P < 0.05). Conclusions Automated quantification of CNFL provides comparable neuropathy detection ability to manual and semiautomated methods. Because of its speed, objectivity, and consistency, fully automated analysis of CNFL might be advantageous in studies of diabetic neuropathy.

Using automated text analysis to evaluate students’ conceptual understanding

Background: A major challenge for assessing students’ conceptual understanding of STEM subjects is the capacity of assessment tools to reliably and robustly evaluate student thinking and reasoning. Multiple-choice tests are typically used to assess student learning and are designed to include distractors that can indicate students’ incomplete understanding of a topic or concept based on which distractor the student selects. However, these tests fail to provide the critical information uncovering the how and why of students’ reasoning for their multiple-choice selections. Open-ended or structured response questions are one method for capturing higher level thinking, but are often costly in terms of time and attention to properly assess student responses. Purpose: The goal of this study is to evaluate methods for automatically assessing open-ended responses, e.g. students’ written explanations and reasoning for multiple-choice selections. Design/Method: We incorporated an open response component for an online signals and systems multiple-choice test to capture written explanations of students’ selections. The effectiveness of an automated approach for identifying and assessing student conceptual understanding was evaluated by comparing results of lexical analysis software packages (Leximancer and NVivo) to expert human analysis of student responses. In order to understand and delineate the process for effectively analysing text provided by students, the researchers evaluated strengths and weakness for both the human and automated approaches. Results: Human and automated analyses revealed both correct and incorrect associations for certain conceptual areas. For some questions, that were not anticipated or included in the distractor selections, showing how multiple-choice questions alone fail to capture the comprehensive picture of student understanding. The comparison of textual analysis methods revealed the capability of automated lexical analysis software to assist in the identification of concepts and their relationships for large textual data sets. We also identified several challenges to using automated analysis as well as the manual and computer-assisted analysis. Conclusions: This study highlighted the usefulness incorporating and analysing students’ reasoning or explanations in understanding how students think about certain conceptual ideas. The ultimate value of automating the evaluation of written explanations is that it can be applied more frequently and at various stages of instruction to formatively evaluate conceptual understanding and engage students in reflective

Automated melanoma diagnosis system

An automated melanoma diagnosis system, the so-called Skin Polar-probe, was developed to improve the chances of early detection of skin cancers and help save the lives of melanoma victims. The system will offer unique benefits to aid early detection of melanoma - the key to reducing deaths caused by this cancer.

Accelerating taxonomic discovery through automated character extraction

This paper discusses the following key messages. Taxonomy is (and taxonomists are) more important than ever in times of global change. Taxonomic endeavour is not occurring fast enough: in 250 years since the creation of the Linnean Systema Naturae, only about 20% of Earth's species have been named. We need fundamental changes to the taxonomic process and paradigm to increase taxonomic productivity by orders of magnitude. Currently, taxonomic productivity is limited principally by the rate at which we capture and manage morphological information to enable species discovery. Many recent (and welcomed) initiatives in managing and delivering biodiversity information and accelerating the taxonomic process do not address this bottleneck. Development of computational image analysis and feature extraction methods is a crucial missing capacity needed to enable taxonomists to overcome the taxonomic impediment in a meaningful time frame. Copyright © 2009 Magnolia Press.

Automated fit quantification of tibial nail designs during the insertion using computer three-dimensional modelling

Intramedullary nailing is the standard fixation method for displaced diaphyseal fractures of the tibia. An optimal nail design should both facilitate insertion and anatomically fit the bone geometry at its final position in order to reduce the risk of stress fractures and malalignments. Due to the nonexistence of suitable commercial software, we developed a software tool for the automated fit assessment of nail designs. Furthermore, we demonstrated that an optimised nail, which fits better at the final position, is also easier to insert. Three-dimensional models of two nail designs and 20 tibiae were used. The fitting was quantified in terms of surface area, maximum distance, sum of surface areas and sum of maximum distances by which the nail was protruding into the cortex. The software was programmed to insert the nail into the bone model and to quantify the fit at defined increment levels. On average, the misfit during the insertion in terms of the four fitting parameters was smaller for the Expert Tibial Nail Proximal bend (476.3 mm2, 1.5 mm, 2029.8 mm2, 6.5 mm) than the Expert Tibial Nail (736.7 mm2, 2.2 mm, 2491.4 mm2, 8.0 mm). The differences were statistically significant (p ≤ 0.05). The software could be used by nail implant manufacturers for the purpose of implant design validation.

Is there a bone-nail specific entry point? automated fit quantification of tibial nail designs during the insertion for six different nail entry points

Intramedullary nailing is the standard fixation method for displaced diaphyseal fractures of tibia. Selection of the correct nail insertion point is important for axial alignment of bone fragments and to avoid iatrogenic fractures. However, the standard entry point (SEP) may not always optimise the bone-nail fit due to geometric variations of bones. This study aimed to investigate the optimal entry for a given bone-nail pair using the fit quantification software tool previously developed by the authors. The misfit was quantified for 20 bones with two nail designs (ETN and ETN-Proximal Bend) related to the SEP and 5 entry points which were 5 mm and 10 mm away from the SEP. The SEP was the optimal entry point for 50% of the bones used. For the remaining bones, the optimal entry point was located 5 mm away from the SEP, which improved the overall fit by 40% on average. However, entry points 10 mm away from the SEP doubled the misfit. The optimised bone-nail fit can be achieved through the SEP and within the range of a 5 mm radius, except posteriorly. The study results suggest that the optimal entry point should be selected by considering the fit during insertion and not only at the final position.

Visual control for automated aircraft collision avoidance systems

This thesis presents a new vision-based decision and control strategy for automated aircraft collision avoidance that can be realistically applied to the See and Avoid problem. The effectiveness of the control strategy positions the research as a major contribution toward realising the simultaneous operation of manned and unmanned aircraft within civilian airspace. Key developments include novel classical and visual predictive control frameworks, and a performance evaluation technique aligned with existing aviation practise and applicable to autonomous systems. The overall approach is demonstrated through experimental results on a small multirotor unmanned aircraft, and through high fidelity probabilistic simulation studies.