Survey of Image Processing Techniques for Brain Pathology Diagnosis: Challenges and Opportunities

In recent years, a number of new products introduced to the global market combine intelligent robotics, artificial intelligence and smart interfaces to provide powerful tools to support professional decision making. However, while brain disease diagnosis from the brain scan images is supported by imaging robotics, the data analysis to form a medical diagnosis is performed solely by highly trained medical professionals. Recent advances in medical imaging techniques, artificial intelligence, machine learning and computer vision present new opportunities to build intelligent decision support tools to aid the diagnostic process, increase the disease detection accuracy, reduce error, automate the monitoring of patient's recovery, and discover new knowledge about the disease cause and its treatment. This article introduces the topic of medical diagnosis of brain diseases from the MRI based images. We describe existing, multi-modal imaging techniques of the brain's soft tissue and describe in detail how are the resulting images are analyzed by a radiologist to form a diagnosis. Several comparisons between the best results of classifying natural scenes and medical image analysis illustrate the challenges of applying existing image processing techniques to the medical image analysis domain. The survey of medical image processing methods also identified several knowledge gaps, the need for automation of image processing analysis, and the identification of the brain structures in the medical images that differentiate healthy tissue from a pathology. This survey is grounded in the cases of brain tumor analysis and the traumatic brain injury diagnoses, as these two case studies illustrate the vastly different approaches needed to define, extract, and synthesize meaningful information from multiple MRI image sets for a diagnosis. Finally, the article summarizes artificial intelligence frameworks that are built as multi-stage, hybrid, hierarchical information processing work-flows and the benefits of applying these models for medical diagnosis to build intelligent physician's aids with knowledge transparency, expert knowledge embedding, and increased analytical quality

Polybenzoxazine-derived N-doped carbon as matrix for powder-based electrocatalysts

In addition to catalytic activity, intrinsic stability, tight immobilization on a suitable electrode surface, and sufficient electronic conductivity are fundamental prerequisites for the long-term operation of particle- and especially powder-based electrocatalysts. We present a novel approach to concurrently address these challenges by using the unique properties of polybenzoxazine (pBO) polymers, namely near-zero shrinkage and high residual-char yield even after pyrolysis at high temperatures. Pyrolysis of a nanocubic prussian blue analogue precursor (Km Mnx [Co(CN)₆]y⋅nH₂O) embedded in a bisphenol A and aniline-based pBO led to the formation of a N-doped carbon matrix modified with MnxCoyOz nanocubes. The obtained electrocatalyst exhibits high efficiency toward the oxygen evolution reaction (OER) and more importantly a stable performance for at least 65 h

Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations

The mid-Holocene (6,000 years ago) is a standard experiment for the evaluation of the simulated response of global climate models using paleoclimate reconstructions. The latest mid-Holocene simulations are a contribution by the Palaeoclimate Model Intercomparison Project (PMIP4) to the current phase of the Coupled Model Intercomparison Project (CMIP6). Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the northern hemisphere and associated shifts in tropical rainfall. Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of -0.3 K, which is -0.2 K cooler that the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Neither this difference nor the improvement in model complexity and resolution seems to improve the realism of the simulations. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on climate sensitivity and feedback strength

Leukoencephalopathy resolution after atypical mycobacterial treatment: a case report

Abstract\ud \ud Background\ud Association of leukoencephalopathy and atypical mycobacteriosis has been rarely reported. We present a case that is relevant for its unusual presentation and because it may shed further light on the pathogenic mechanisms underlying reversible encephalopathies.\ud \ud \ud Case report\ud We report the case of a Hispanic 64-year-old woman with cognitive decline and extensive leukoencephalopathy. Magnetic resonance imaging revealed white-matter lesions with increased water diffusivity, without blood–brain-barrier disruption. Brain biopsy showed tissue rarefaction with vacuolation, mild inflammation, few reactive astrocytes and decreased aquaporin water-channel expression in the lesions. Six months later, she was diagnosed with atypical mycobacterial pulmonary infection. Brain lesions resolved after antimycobacterial treatment.\ud \ud \ud Conclusion\ud We hypothesize leukoencephalopathic changes and vasogenic edema were associated with decreased aquaporin expression. Further studies should clarify if reversible leukoencephalopathy has a causal relationship with decreased aquaporin expression and atypical mycobacterial infection, and mechanisms underlying leukoencephalopathy resolution after antimycobacterial treatment. This article may contribute to the understanding of pathogenic mechanisms underlying magnetic resonance imaging subcortical lesions and edema, which remain incompletely understood.Ministry of Education, Culture, Sports, Science and Technology (MEXT) of JapanHealth and Labor Sciences Research Grant on Intractable Diseases\ud (Neuroimmunological Diseases) from the Ministry of Health, Labor and\ud Welfare of Japa

Crowdsourcing and the feasibility of manual gene annotation: A pilot study in the nematode Pristionchus pacificus

Nematodes such as Caenorhabditis elegans are powerful systems to study basically all aspects of biology. Their species richness together with tremendous genetic knowledge from C. elegans facilitate the evolutionary study of biological functions using reverse genetics. However, the ability to identify orthologs of candidate genes in other species can be hampered by erroneous gene annotations. To improve gene annotation in the nematode model organism Pristionchus pacificus, we performed a genome-wide screen for C. elegans genes with potentially incorrectly annotated P. pacificus orthologs. We initiated a community-based project to manually inspect more than two thousand candidate loci and to propose new gene models based on recently generated Iso-seq and RNA-seq data. In most cases, misannotation of C. elegans orthologs was due to artificially fused gene predictions and completely missing gene models. The community-based curation raised the gene count from 25,517 to 28,036 and increased the single copy ortholog completeness level from 86% to 97%. This pilot study demonstrates how even small-scale crowdsourcing can drastically improve gene annotations. In future, similar approaches can be used for other species, gene sets, and even larger communities thus making manual annotation of large parts of the genome feasible