Synergic Deep Learning for Smart Health Diagnosis of COVID-19 for Connected Living and Smart Cities

COVID-19 pandemic has led to a significant loss of global deaths, economical status, and so on. To prevent and control COVID-19, a range of smart, complex, spatially heterogeneous, control solutions, and strategies have been conducted. Earlier classification of 2019 novel coronavirus disease (COVID-19) is needed to cure and control the disease. It results in a requirement of secondary diagnosis models, since no precise automated toolkits exist. The latest finding attained using radiological imaging techniques highlighted that the images hold noticeable details regarding the COVID-19 virus. The application of recent artificial intelligence (AI) and deep learning (DL) approaches integrated to radiological images finds useful to accurately detect the disease. This article introduces a new synergic deep learning (SDL)-based smart health diagnosis of COVID-19 using Chest X-Ray Images. The SDL makes use of dual deep convolutional neural networks (DCNNs) and involves a mutual learning process from one another. Particularly, the representation of images learned by both DCNNs is provided as the input of a synergic network, which has a fully connected structure and predicts whether the pair of input images come under the identical class. Besides, the proposed SDL model involves a fuzzy bilateral filtering (FBF) model to pre-process the input image. The integration of FBL and SDL resulted in the effective classification of COVID-19. To investigate the classifier outcome of the SDL model, a detailed set of simulations takes place and ensures the effective performance of the FBF-SDL model over the compared methods.

Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy

Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment.

Combined Use of Multiple Intravascular Imaging Techniques in Acute Coronary Syndrome

Recent advances in intravascular imaging techniques have made it possible to assess the culprit lesions of acute coronary syndrome (ACS) in the clinical setting. Intravascular ultrasound (IVUS) is the most commonly used intravascular imaging technique that provides cross-sectional images of coronary arteries. IVUS can assess plaque burden and vessel remodeling. Optical coherence tomography (OCT) is a high-resolution (10 μm) intravascular imaging technique that uses near-infrared light. OCT can identify key features of atheroma, such as lipid core and thin fibrous cap. Near-infrared spectroscopy (NIRS) can detect lipid composition by analyzing the near-infrared absorption properties of coronary plaques. NIRS provides a chemogram of the coronary artery wall, which allows for specific quantification of lipid accumulation. These intravascular imaging techniques can depict histological features of plaque rupture, plaque erosion, and calcified nodule in ACS culprit lesions. However, no single imaging technique is perfect and each has its respective strengths and limitations. In this review, we summarize the implications of combined use of multiple intravascular imaging techniques to assess the pathology of ACS and guide lesion-specific treatment.

Stimulus techniques and microelectrode recordings of subthalamic-nuclei neurons in Parkinson`s during functional-neurosurgery

This study discusses the various procedures and issues involved in the acquisition of microelectrode recordings (MER) signals of subthalamic nucleus stimulations with induced deep brain stimulation electrodes very rigorously. Bellicose-invasive physiological detections through the methods of sub cortical physio logical detections, electrical induced stimulations and micro electrode recordings, stereo-tactic technique, macro-stimulation, stereo-tactic functional neurosurgical technique, stimulations such as macro and micro, induced stimuli with current and microelectrode recordings, impedance information monitoring, micro injections of test substances, evoked potentials, biomarkers/local field potentials, microelectrode fabrication methods and setups, sub cortical atlas-mapping with micro recording/microelectrode recording (M.E.R.). Thus, the study is very significant to the electrophysiological neurosurgical point of view and is very useful to the field of microelectrode recording and functional neurosurgery. This study is concerned with invasive physiological detection of deep brain structures with micro- or macro-electrodes prior to surgery followed by imaging techniques and their use in cortical and subcortical detection; detection relevant to the superficial cerebral cortex regions.

Medulloblastoma Presenting as Severe Headache during Pregnancy: A Case Report and Review of the Literature

Headache is a common complaint during pregnancy and the puerperium. The differentiation between a benign headache and a headache that has an underlying more endangering cause, such as an intracranial tumor, can be difficult and often requires diagnostic procedures and brain imaging techniques. We report the case of an 18-year-old female patient who developed clinical symptoms—persistent headache followed by neurological deficit—in the last part of her pregnancy. A medulloblastoma (MB) was diagnosed and treated after delivery. We review 11 other cases of MB in pregnancy reported in the literature. The most common clinical manifestation at diagnosis was headache followed by neurological deficits. We discuss the association of brain tumor growth with physiological changes during pregnancy. We conclude that clinical features of intracranial tumors can be misinterpreted as pregnancy-related symptoms and should not be dismissed.

Osseous Infections Caused by Aspergillus Species

Background: Osteomyelitis caused by Aspergillus spp. is a severe, but rare, clinical entity. However, clear guidelines regarding the most effective medical management have not yet been established. The present study is a literature review of all such cases, in an effort to elucidate epidemiology, as well as the therapeutic management and the infection’s outcome. Methods: A thorough review of all reports of osteomyelitis of the appendicular and the axial skeleton, without the skull and the spine, caused by Aspergillus spp. was undertaken. Data about demographics, imaging techniques facilitating diagnosis, causative Aspergillus, method of mold isolation, antifungal treatment (AFT), surgical treatment, as well as the infection’s outcome were recorded and evaluated. Results: A total of 63 cases of osseous infection due to Aspergillus spp. were identified. The studied population’s mean age was 37.9 years. The most commonly affected site was the rib cage (36.8%). Most hosts suffered immunosuppressive conditions (76.2%). Regarding imaging methods indicating diagnosis, computer tomography (CT) was performed in most cases (42.9%), followed by plain X-ray (41.3%) and magnetic resonance imaging (MRI) (34.9%). The most frequent isolated mold was Aspergillus fumigatus (49.2%). Cultures and/or histopathology were used for definite diagnosis in all cases, while galactomannan antigen test was additionally used in seven cases (11.1%), polymerase chain reaction (PCR) in four cases (6.3%), and beta-d-glucan testing in three cases (4.8%). Regarding AFT, the preferred antifungal was voriconazole (61.9%). Most patients underwent surgical debridement (63.5%). The outcome was successful in 77.5%. Discussion: Osteomyelitis due to Aspergillus spp. represents a severe infection. The available data suggest that prolonged AFT in combination with surgical debridement is the preferred management of this infection, while identification of the responsible mold is of paramount importance.

Tumor Reduction in Multiple Myeloma: New Concepts for New Therapeutics

The development of new resources for a more accurate diagnosis and response assessment in multiple myeloma has been a long process for decades, mainly since the middle of the 20th century. During this time, the succession of technical advances has run parallel to the better knowledge of disease biology and the availability of novel therapeutic strategies. The cornerstone of standardized criteria to uniformly evaluate the disease response in myeloma dates back to the 1990s when the key role of complete remission was established. Since then, different updates have been implemented according to available scientific evidences not always without certain controversies. The progressive improvements in survival results of myeloma patients and the growing quality of responses due to the novel therapies have led to the need of developing new tools for better monitoring of tumor burden. In this way, the concept of minimal residual disease and its key value based on the prognostic significance and the clinical relevance has been consolidated during the last years, overcoming the value of conventional response criteria or classical adverse prognosis markers. Nevertheless, its precise role in the clinical management of myeloma patients to detect early treatment failure and trigger early rescue strategies is still pending to be defined. In this review, we revisit the major milestones in the understanding of tumor reduction in multiple myeloma until the most recent imaging techniques or liquid biopsy approaches, including a critical view of conventional response criteria, whose backbone has remained unchanged during the last 20 years.

Ground Penetrating Radar Algorithm to Sense the Depth of Blood Clot in Microwave Head Imaging

Background: Microwave imaging is one of the emerging non-invasive portable imaging techniques, which uses nonionized radiations to take a detailed view of biological tissues in the microwave frequency range. Brain stroke is an emergency caused by the interruption of the blood supply into parts of brain, leading to the loss of millions of brain cells. Imaging plays a major role in stroke diagnosis for prompt treatment. Objective: This work proposes a computationally efficient algorithm called the GPR algorithm to locate the blood clot with a size of 10 mm in microwave images. Methods: The electromagnetic waves are radiated, and backscattered reflections are received by Antipodal Vivaldi antenna with the parasitic patch (48 mm*21 mm). The received signals are converted to a planar 2D image, and the depth of the blood clot is identified from the B-scan image. The novelty of this work lies in applying the GPR algorithm for the accurate positioning of a blood clot in a multilayered head tissue. Results: The proposed system is effectively demonstrated using a 3D EM simulator and simulated results are verified in a Vector network analyzer (E8363B) with an experimental setup. Conclusion: This an alternative safe imaging modality compared to present imaging systems(CT and MRI)

MIA: An Open Source Standalone Deep Learning Application for Microscopic Image Analysis

In recent years the amount of data generated by imaging techniques has grown rapidly along with increasing computational power and the development of deep learning algorithms. To address the need for powerful automated image analysis tools for a broad range of applications in the biomedical sciences, we present the Microscopic Image Analyzer (MIA). MIA combines a graphical user interface that obviates the need for programming skills with state-of-the-art deep learning algorithms for segmentation, object detection, and classification. It runs as a standalone, platform-independent application and is compatible with commonly used open source software packages. The software provides a unified interface for easy image labeling, model training and inference. Furthermore the software was evaluated in a public competition and performed among the top three for all tested data sets. The source code is available on https://github.com/MIAnalyzer/MIA.

Thermographic Screening of Beef Cattle Metatarsal Growth Plate Lesions

Lameness represents one of the main causes of decreased productive performance and impaired animal welfare in the bovine industry. Young beef bulls are predisposed to develop diseases of the growing skeleton, especially growth plate lesions. Early diagnosis is indispensable for ensuring correct treatment, fast recovery and reduction losses. However, when dealing with beef cattle, this is not always possible. Fast and reliable diagnostic imaging techniques are necessary to improve dealing with lameness in beef animals. The aim of the present study was to examine the potential of thermographic imaging as a non-invasive tool for rapidly screening beef bulls for the presence of growth plate lesions. Here, 20 Charolais and Limousine beef bulls affected by growth plate lesions in one of the rear limbs were selected. IRT was performed on both hind limbs using a digital infrared camera (ThermaCam T420 Model, Flir Systems, Boston, MA, USA), prior to radiographic imaging and clinical examination. The temperature of healthy and affected limbs was measured in two regions: the area correspondent to the growth plate (AR01) and the whole area of the metatarsus (AR02). Growth plate lesions were found to increase the maximum, mean, and minimum temperatures in AR01; and the mean and maximum temperatures in AR02, therefore, indicating the potential of IRT as a reliable, practical tool for screening growth plate lesions in beef bulls.