A digital imaging technique to quantify the incidence of internal browning in potato (Solanum tuberosum) tubers

Internal browning disorders, including brown fleck (BF), in potato (Solanum tuberosum) tubers greatly reduce tuber quality, but the causes are not well understood. This is due, in part, to the highly variable data provided by visual value-based rating systems. A digital imaging technique was developed to quantify accurately the incidence of internal browning in potato tubers. Images of tuber sections were scanned using a flatbed scanner and digitally enhanced to highlight tuber BF lesions, and the area of affected tissue calculated using pixel quantification software. Digital imaging allowed for the determination of previously unused indices of the incidence and severity of internal browning in potato tubers. Statistical analysis of the comparison between digitally derived and visual-rating BF data from a glasshouse experiment showed that digital data greatly improved the delineation of treatment effects. The F-test probability was further improved through square root or logarithmic data transformations of the digital data, but not of the visual-rating data. Data from a field experiment showed that the area of tuber affected by BF and the number of small BF lesions increased with time and with increase in tuber size. The results from this study indicate that digital imaging of internal browning disorders of potato tubers holds much promise in determining their causes that heretofore have proved elusive.

Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis.

The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images. PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses.

Developmental, functional brain imaging and electrophysiological evidence of visual and auditory working memory

Intact function of working memory (WM) is essential for children and adults to cope with every day life. Children with deficits in WM mechanisms have learning difficulties that are often accompanied by behavioral problems. The neural processes subserving WM, and brain structures underlying this system, continue to develop during childhood till adolescence and young adulthood. With functional magnetic resonance imaging (fMRI) it is possible to investigate the organization and development of WM. The present thesis aimed to investigate, using behavioral and neuroimaging methods, whether mnemonic processing of spatial and nonspatial visual information is segregated in the developing and mature human brain. A further aim in this research was to investigate the organization and development of audiospatial and visuospatial information processing in WM. The behavioral results showed that spatial and nonspatial visual WM processing is segregated in the adult brain. The fMRI result in children suggested that memory load related processing of spatial and nonspatial visual information engages common cortical networks, whereas selective attention to either type of stimuli recruits partially segregated areas in the frontal, parietal and occipital cortices. Deactivation mechanisms that are important in the performance of WM tasks in adults are already operational in healthy school-aged children. Electrophysiological evidence suggested segregated mnemonic processing of visual and auditory location information. The results of the development of audiospatial and visuospatial WM demonstrate that WM performance improves with age, suggesting functional maturation of underlying cognitive processes and brain areas. The development of the performance of spatial WM tasks follows a different time course in boys and girls indicating a larger degree of immaturity in the male than female WM systems. Furthermore, the differences in mastering auditory and visual WM tasks may indicate that visual WM reaches functional maturity earlier than the corresponding auditory system. Spatial WM deficits may underlie some learning difficulties and behavioral problems related to impulsivity, difficulties in concentration, and hyperactivity. Alternatively, anxiety or depressive symptoms may affect WM function and the ability to concentrate, being thus the primary cause of poor academic achievement in children.

Multispectral imaging and genomic mapping

Identifying QTLs linked to malting and protein levels in barley using multispectral image data.

Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision

There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

Infrared thermal imaging for automated detection of diabetic foot complications

Background Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. Methods The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had difuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). Results No diferences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with difuse complications, mean temperature diferences of >3 °C between ipsilateral and contralateral foot were found. Conclusions With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or difuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings.

Assessment of signs of foot infection in diabetes patients using photographic foot imaging and infrared thermography

Background Patients with diabetic foot disease require frequent screening to prevent complications and may be helped through telemedical home monitoring. Within this context, the goal was to determine the validity and reliability of assessing diabetic foot infection using photographic foot imaging and infrared thermography. Subjects and Methods For 38 patients with diabetes who presented with a foot infection or were admitted to the hospital with a foot-related complication, photographs of the plantar foot surface using a photographic imaging device and temperature data from six plantar regions using an infrared thermometer were obtained. A temperature difference between feet of > 2.2 °C defined a ''hotspot.'' Two independent observers assessed each foot for presence of foot infection, both live (using the Perfusion-Extent-Depth- Infection-Sensation classification) and from photographs 2 and 4 weeks later (for presence of erythema and ulcers). Agreement in diagnosis between live assessment and (the combination of ) photographic assessment and temperature recordings was calculated. Results Diagnosis of infection from photographs was specific (> 85%) but not very sensitive (< 60%). Diagnosis based on hotspots present was sensitive (> 90%) but not very specific (<25%). Diagnosis based on the combination of photographic and temperature assessments was both sensitive (> 60%) and specific (> 79%). Intra-observer agreement between photographic assessments was good (Cohen's j = 0.77 and 0.52 for both observers). Conclusions Diagnosis of foot infection in patients with diabetes seems valid and reliable using photographic imaging in combination with infrared thermography. This supports the intended use of these modalities for the home monitoring of high-risk patients with diabetes to facilitate early diagnosis of signs of foot infection.

Pseudo-time marching schemes for inverse problems in structural health assessment and medical imaging

We propose a self-regularized pseudo-time marching strategy for ill-posed, nonlinear inverse problems involving recovery of system parameters given partial and noisy measurements of system response. While various regularized Newton methods are popularly employed to solve these problems, resulting solutions are known to sensitively depend upon the noise intensity in the data and on regularization parameters, an optimal choice for which remains a tricky issue. Through limited numerical experiments on a couple of parameter re-construction problems, one involving the identification of a truss bridge and the other related to imaging soft-tissue organs for early detection of cancer, we demonstrate the superior features of the pseudo-time marching schemes.

Blended learning in medical imaging pre-clinical skills training – does it work?

Undergraduate Medical Imaging (MI)students at QUT attend their first clinical placement towards the end of semester two. Students undertake two (pre)clinical skills development units – one theory and one practical. Students gain good contextual and theoretical knowledge during these units via a blended learning model with multiple learning methods employed. Students attend theory lectures, practical sessions, tutorial sessions in both a simulated and virtual environment and also attend pre-clinical scenario based tutorial sessions. The aim of this project is to evaluate the use of blended learning in the context of 1st year Medical Imaging Radiographic Technique and its effectiveness in preparing students for their first clinical experience. It is hoped that the multiple teaching methods employed within the pre-clinical training unit at QUT builds students clinical skills prior to the real situation. A quantitative approach will be taken, evaluating via pre and post clinical placement surveys. This data will be correlated with data gained in the previous year on the effectiveness of this training approach prior to clinical placement. In 2014 59 students were surveyed prior to their clinical placement demonstrated positive benefits of using a variety of learning tools to enhance their learning. 98.31%(n=58)of students agreed or strongly agreed that the theory lectures were a useful tool to enhance their learning. This was followed closely by 97% (n=57) of the students realising the value of performing role-play simulation prior to clinical placement. Tutorial engagement was considered useful for 93.22% (n=55) whilst 88.14% (n=52) reasoned that the x-raying of phantoms in the simulated radiographic laboratory was beneficial. Self-directed learning yielded 86.44% (n=51). The virtual reality simulation software was valuable for 72.41% (n=42) of the students. Of the 4 students that disagreed or strongly disagreed with the usefulness of any tool they strongly agreed to the usefulness of a minimum of one other learning tool. The impact of the blended learning model to meet diverse student needs continues to be positive with students engaging in most offerings. Students largely prefer pre -clinical scenario based practical and tutorial sessions where 'real-world’ situations are discussed.

Microsurgical Aneurysm Model in Rats and Mice: Development of Endovascular Treatment and Optimization of Magnetic Resonance Imaging

The rupture of a cerebral artery aneurysm causes a devastating subarachnoid hemorrhage (SAH), with a mortality of almost 50% during the first month. Each year, 8-11/100 000 people suffer from aneurysmal SAH in Western countries, but the number is twice as high in Finland and Japan. The disease is most common among those of working age, the mean age at rupture being 50-55 years. Unruptured cerebral aneurysms are found in 2-6% of the population, but knowledge about the true risk of rupture is limited. The vast majority of aneurysms should be considered rupture-prone, and treatment for these patients is warranted. Both unruptured and ruptured aneurysms can be treated by either microsurgical clipping or endovascular embolization. In a standard microsurgical procedure, the neck of the aneurysm is closed by a metal clip, sealing off the aneurysm from the circulation. Endovascular embolization is performed by packing the aneurysm from the inside of the vessel lumen with detachable platinum coils. Coiling is associated with slightly lower morbidity and mortality than microsurgery, but the long-term results of microsurgically treated aneurysms are better. Endovascular treatment methods are constantly being developed further in order to achieve better long-term results. New coils and novel embolic agents need to be tested in a variety of animal models before they can be used in humans. In this study, we developed an experimental rat aneurysm model and showed its suitability for testing endovascular devices. We optimized noninvasive MRI sequences at 4.7 Tesla for follow-up of coiled experimental aneurysms and for volumetric measurement of aneurysm neck remnants. We used this model to compare platinum coils with polyglycolic-polylactic acid (PGLA) -coated coils, and showed the benefits of the latter in this model. The experimental aneurysm model and the imaging methods also gave insight into the mechanisms involved in aneurysm formation, and the model can be used in the development of novel imaging techniques. This model is affordable, easily reproducible, reliable, and suitable for MRI follow-up. It is also suitable for endovascular treatment, and it evades spontaneous occlusion.