287 research outputs found
Anatomical Data Augmentation For CNN based Pixel-wise Classification
In this work we propose a method for anatomical data augmentation that is
based on using slices of computed tomography (CT) examinations that are
adjacent to labeled slices as another resource of labeled data for training the
network. The extended labeled data is used to train a U-net network for a
pixel-wise classification into different hepatic lesions and normal liver
tissues. Our dataset contains CT examinations from 140 patients with 333 CT
images annotated by an expert radiologist. We tested our approach and compared
it to the conventional training process. Results indicate superiority of our
method. Using the anatomical data augmentation we achieved an improvement of 3%
in the success rate, 5% in the classification accuracy, and 4% in Dice.Comment: To be presented at IEEE ISBI 201
Surgical emergencies confounded by H1N1 influenza infection - a plea for concern
The outbreak of the H1N1 influenza pandemic resulted in unprecedented, overwhelming exposure in the medical and lay media, with the obvious focus of healthcare providers being on patients in internal medicine or intensive care settings. Recently, we treated 3 patients with various surgical emergencies who were also diagnosed with active H1N1 influenza. The purpose of this report is to bring the issue of H1N1 flu in association with surgical emergencies to the forefront of the literature, and suggest that surgical diseases might be significantly accentuated in patients with H1N1 influenza
Barrier-Restoring Therapies in Atopic Dermatitis: Current Approaches and Future Perspectives
Atopic dermatitis is a multifactorial, chronic relapsing, inflammatory disease, characterized by xerosis, eczematous lesions, and pruritus. The latter usually leads to an “itch-scratch” cycle that may compromise the epidermal barrier. Skin barrier abnormalities in atopic dermatitis may result from mutations in the gene encoding for filaggrin, which plays an important role in the formation of cornified cytosol. Barrier abnormalities render the skin more permeable to irritants, allergens, and microorganisms. Treatment of atopic dermatitis must be directed to control the itching, suppress the inflammation, and restore the skin barrier. Emollients, both creams and ointments, improve the barrier function of stratum corneum by providing it with water and lipids. Studies on atopic dermatitis and barrier repair treatment show that adequate lipid replacement therapy reduces the inflammation and restores epidermal function. Efforts directed to develop immunomodulators that interfere with cytokine-induced skin barrier dysfunction, provide a promising strategy for treatment of atopic dermatitis. Moreover, an impressive proliferation of more than 80 clinical studies focusing on topical treatments in atopic dermatitis led to growing expectations for better therapies
Witness: The Modern Writer as Witness
Editor\u27s Note [Excerpt] The United States, as a society, is on the brink of profound and positive change. Demographically and culturally, things are improving, and the reason is obvious to people who study history: Conflict pushes us to be better, to strive for principled goals. Consider the inspired eco-advocacy of Greta Thunberg. Or the swearing in of most diverse class of lawmakers in history into the 116th Congress. Or billionaire Robert F. Smith’s pledge to pay off every Morehouse College (in Atlanta, Georgia) student’s debt. Indeed, there are many good people helping and great moments happening in spite of a bleak 24-hour news cycle designed to ruin happiness and to limit our understanding of our human potential. We at Witness see this yearning for transformation in the works we selected. The doorway must be crossed, and the voices and characters we featured in our Winter 2019 issue stand at the vestibule, ready for the light to warm them, primed to fight for that necessary illumination.https://digitalscholarship.unlv.edu/witness/1000/thumbnail.jp
Effect of IGF-I on Hair Growth Is Related to the Anti-Apoptotic Effect of IGF-I and Up-Regulation of PDGF-A and PDGF-B
Self-reported neurological symptoms in relation to CO emissions due to problem gas appliance installations in London: a cross-sectional survey
Background: Previous research by the authors found evidence that up to 10% of particular household categories may be exposed to elevated carbon monoxide (CO) concentrations from poor quality gas appliance installations. The literature suggests certain neurological symptoms are linked to exposure to low levels of CO. This paper addresses the hypothesis that certain self-reported neurological symptoms experienced by a householder are linked to an estimate of their CO exposure.Methods: Between 27 April and 27 June 2006, 597 homes with a mains supply of natural gas were surveyed, mainly in old, urban areas of London. Qualified gas engineers tested all gas appliances (cooker, boiler, gas fire, and water heater) and reported, according to the Gas Industry Unsafe Situations Procedure, appliances considered At Risk (AR), Immediately Dangerous (ID) or Not to Current Standards (NCS). Five exposure risk categories were defined based on measurement of CO emitted by the appliance, its features and its use, with "high or very high" exposure category where occupants were considered likely to be exposed to levels greater than 26 ppm for one hour. The prevalence of symptoms at each level of exposure was compared with that at lowest level of exposure.Results: Of the households, 6% were assessed as having a "high or very high" risk of exposure to CO. Of the individuals, 9% reported at least one neurological symptom. There was a statistically significant association between "high or very high" exposure risk to CO and self-reported symptoms compared to "no exposure" likelihood, for households not in receipt of benefit, controlling for "number of residents" and presence of pensioners, OR = 3.23 (95% CI: 1.28, 8.15). Risk ratios across all categories of exposure likelihood indicate a dose-response pattern. Those households in receipt of benefit showed no dose-response pattern.Conclusion: This study found an association between risk of CO exposure at low concentration, and prevalence of self-reported neurological symptoms in the community for those households not in receipt of benefit. As health status was self-reported, this association requires further investigation
The Experiment That did not Fail: Image and Reality in the Israeli Kibbutz
The kibbutzim of Israel show the world that communal living can be successful, and many observers have asked the questions: Can this success be repeated elsewhere? What are its lessons for other societies? In sociology, the validity and importance of comparative study and the intrinsic interest of the kibbutz way of life cannot be denied
The Liver Tumor Segmentation Benchmark (LiTS)
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://medicaldecathlon.com/. In addition, both data and online evaluation are accessible via https://competitions.codalab.org/competitions/17094
Magnetic resonance enterography in pregnant women with Crohn’s disease: case series and literature review
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