Automated Segmentation of Pulmonary Lobes using Coordination-Guided Deep Neural Networks

The identification of pulmonary lobes is of great importance in disease diagnosis and treatment. A few lung diseases have regional disorders at lobar level. Thus, an accurate segmentation of pulmonary lobes is necessary. In this work, we propose an automated segmentation of pulmonary lobes using coordination-guided deep neural networks from chest CT images. We first employ an automated lung segmentation to extract the lung area from CT image, then exploit volumetric convolutional neural network (V-net) for segmenting the pulmonary lobes. To reduce the misclassification of different lobes, we therefore adopt coordination-guided convolutional layers (CoordConvs) that generate additional feature maps of the positional information of pulmonary lobes. The proposed model is trained and evaluated on a few publicly available datasets and has achieved the state-of-the-art accuracy with a mean Dice coefficient index of 0.947 $\pm$ 0.044.Comment: ISBI 2019 (Oral

Applications of Artificial Intelligence in Battling Against Covid-19: A Literature Review

© 2020 Elsevier Ltd. All rights reserved.Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of grave concern for every country around the world. The rapid growth of the pandemic has wreaked havoc and prompted the need for immediate reactions to curb the effects. To manage the problems, many research in a variety of area of science have started studying the issue. Artificial Intelligence is among the area of science that has found great applications in tackling the problem in many aspects. Here, we perform an overview on the applications of AI in a variety of fields including diagnosis of the disease via different types of tests and symptoms, monitoring patients, identifying severity of a patient, processing covid-19 related imaging tests, epidemiology, pharmaceutical studies, etc. The aim of this paper is to perform a comprehensive survey on the applications of AI in battling against the difficulties the outbreak has caused. Thus we cover every way that AI approaches have been employed and to cover all the research until the writing of this paper. We try organize the works in a way that overall picture is comprehensible. Such a picture, although full of details, is very helpful in understand where AI sits in current pandemonium. We also tried to conclude the paper with ideas on how the problems can be tackled in a better way and provide some suggestions for future works.Peer reviewe

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

Mapping the Impact and Plasticity of Cortical-Cardiovascular Interactions in Vascular Disease Using Structural and Functional MRI

There is growing interest in the role of vascular disease in accelerating age-related decline in cerebrovascular structural and functional integrity. Since an increased number of older adults are surviving chronic diseases, of which cardiovascular disease (CVD) is prevalent, there is an urgent need to understand relationships between cardiovascular dysfunction and brain health. It is unclear if CVD puts the brains of older adults, already experiencing natural brain aging, at greater risk for degeneration. In this thesis, the role of CVD in accelerating brain aging is explored. Because physical activity is known to provide neuroprotective benefits to brains of older adults, the role of physical activity in mediating disease effects were also explored. Using novel neuroimaging techniques, measures of gray matter volume and cerebrovascular hemodynamics were compared between groups of coronary artery disease patients and age-matched controls, to describe regional effects of CVD on the brain. In a sub-set of patients, imaging measures were repeated after completion of a 6-month exercise training, part of a cardiac rehabilitation program, to examine exercise effects. Differences in cerebrovascular hemodynamics were measured as changes in resting cerebral blood flow (CBF) and changes in cerebrovascular reactivity (CVR) to hypercapnia (6% CO2) using a non-invasive perfusion magnetic resonance imaging technique, arterial spin labelling (ASL). We found decreased brain volume, CBF and CVR in several regions of the brains of coronary artery disease patients compared to age-matched healthy controls. The reductions in CBF and CVR were independent of underlying brain atrophy, suggesting that changes in cerebrovascular function could precede changes in brain structure. In addition, increase in brain volume and CBF were observed in some regions of the brain after exercise training, indicating that cardiac rehabilitation programs may have neurorehabiliation effects as well. Since, CBF measured with ASL is not the [gold] standard measure of functional brain activity, we examined the regional correlation of ASL-CBF to glucose consumption rates (CMRglc) measured with positron emission tomography (PET), a widely acceptable marker of brain functional activity. Simultaneous measurements of ASL-CBF and PET-CMRglc were performed in a separate study in a group of older adults with no neurological impairment. Across brain regions, ASL-CBF correlated well with PET-CMRglc, but variations in regional coupling were found and demonstrate the role of certain brain regions in maintaining higher level of functional organization compared to other regions. In general, the results of the thesis demonstrate the impact of CVD on brain health, and the neurorehabiliation capacity of cardiac rehabilitation. The work presented also highlights the ability of novel non-invasive neuroimaging techniques in detecting and monitoring subtle but robust changes in the aging human brain

Shape analysis of the human brain.

Autism is a complex developmental disability that has dramatically increased in prevalence, having a decisive impact on the health and behavior of children. Methods used to detect and recommend therapies have been much debated in the medical community because of the subjective nature of diagnosing autism. In order to provide an alternative method for understanding autism, the current work has developed a 3-dimensional state-of-the-art shape based analysis of the human brain to aid in creating more accurate diagnostic assessments and guided risk analyses for individuals with neurological conditions, such as autism. Methods: The aim of this work was to assess whether the shape of the human brain can be used as a reliable source of information for determining whether an individual will be diagnosed with autism. The study was conducted using multi-center databases of magnetic resonance images of the human brain. The subjects in the databases were analyzed using a series of algorithms consisting of bias correction, skull stripping, multi-label brain segmentation, 3-dimensional mesh construction, spherical harmonic decomposition, registration, and classification. The software algorithms were developed as an original contribution of this dissertation in collaboration with the BioImaging Laboratory at the University of Louisville Speed School of Engineering. The classification of each subject was used to construct diagnoses and therapeutic risk assessments for each patient. Results: A reliable metric for making neurological diagnoses and constructing therapeutic risk assessment for individuals has been identified. The metric was explored in populations of individuals having autism spectrum disorders, dyslexia, Alzheimers disease, and lung cancer. Conclusion: Currently, the clinical applicability and benefits of the proposed software approach are being discussed by the broader community of doctors, therapists, and parents for use in improving current methods by which autism spectrum disorders are diagnosed and understood

Advanced neuroimaging techniques to study the development of the cerebral cortex, subplate and thalamus in preterm infants at 3 Tesla

Preterm infants are at increased risk of neurodevelopmental delay, cognitive dysfunction, and behavioural disturbances. Recent studies of older preterm children with cognitive impairments implicate morphological and functional cortical abnormalities. However elucidation of the preterm cortical abnormalities has been challenging due to specific neonatal features. Using 3 Tesla neonatal MR images and Expectation Maximisation/Markov Random Field segmentation with incorporation of a novel knowledge based technique for removal of mislabelled partial volume voxels, neonatal 3D cortical extraction was possible from 25 to 48 weeks gestation. This enabled the study of the true cortical scaling exponent, cortical thickness, regional volumes and curvature measurements. It showed a relative excess of the cortical surface area for its volume which corresponded with a change in the intrinsic curvature and fissuration up to 36 weeks gestation, after which, the relative growth of the surface area and volume were proportional leading to dominant changes in the extrinsic curvature and cortical folding. Thus the curvature measurements showed an important mechanistic property of convolution. By term equivalent age, the cortex was thicker and there were changes in cortical curvature although there were no differences in the cortical surface area of preterm infants compared to term born controls. There were specific frontal and parietal deficits in the cortical volume. Diffusion MR showed that although the early cortical anisotropy diminished to noise levels by 35 weeks, the mean diffusivity reduced during the entire third trimester due to changes in the radial diffusivity. Regional variations in the mean diffusivity occurred during development with frontal abnormalities persisting at term equivalent age. Subplate and thalamic quantification showed important development features during the third trimester, however in the absence of overt lesions no associations with cortical measures were found. Thus this thesis provides interesting and novel insights into the macroscopic and microscopic development of the cortex.Imperial Users onl