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1.
Med Image Anal ; 59: 101570, 2020 01.
Article in English | MEDLINE | ID: mdl-31630011

ABSTRACT

Glaucoma is one of the leading causes of irreversible but preventable blindness in working age populations. Color fundus photography (CFP) is the most cost-effective imaging modality to screen for retinal disorders. However, its application to glaucoma has been limited to the computation of a few related biomarkers such as the vertical cup-to-disc ratio. Deep learning approaches, although widely applied for medical image analysis, have not been extensively used for glaucoma assessment due to the limited size of the available data sets. Furthermore, the lack of a standardize benchmark strategy makes difficult to compare existing methods in a uniform way. In order to overcome these issues we set up the Retinal Fundus Glaucoma Challenge, REFUGE (https://refuge.grand-challenge.org), held in conjunction with MICCAI 2018. The challenge consisted of two primary tasks, namely optic disc/cup segmentation and glaucoma classification. As part of REFUGE, we have publicly released a data set of 1200 fundus images with ground truth segmentations and clinical glaucoma labels, currently the largest existing one. We have also built an evaluation framework to ease and ensure fairness in the comparison of different models, encouraging the development of novel techniques in the field. 12 teams qualified and participated in the online challenge. This paper summarizes their methods and analyzes their corresponding results. In particular, we observed that two of the top-ranked teams outperformed two human experts in the glaucoma classification task. Furthermore, the segmentation results were in general consistent with the ground truth annotations, with complementary outcomes that can be further exploited by ensembling the results.


Subject(s)
Deep Learning , Diagnostic Techniques, Ophthalmological , Fundus Oculi , Glaucoma/diagnostic imaging , Photography , Datasets as Topic , Humans
2.
J Environ Sci (China) ; 24(3): 494-8, 2012.
Article in English | MEDLINE | ID: mdl-22655364

ABSTRACT

Aqueous ammonia (NH3) solution can be used as an alternative absorption for the control of CO2 emitted from flue gases due to its high absorption capacity, fast absorption rate and low corrosion problem. The emission of CO2 from iron and steel plants requires much attention, as they are higher than those emitted from power plants at a single point source. In the present work, low concentration ammonia liquor, 9 wt.%, was used with various additives to obtain the kinetic properties using the blast furnace gas model. Although a solution with a high ammonia concentration enables high CO2 absorption efficiency, ammonium ions are lost as ammonia vapor, resulting in reduced CO2 absorption due to the lower concentration of the ammonia absorbent. To decrease the vaporization of ammonia, ethylene glycol, glycerol and glycine, which contain more than one hydroxyl radical, were chosen. The experiments were conducted at 313 K similar to the CO2 absorption conditions for the blast furnace gas model.


Subject(s)
Ammonia/chemistry , Carbon Dioxide/chemistry , Ethylene Glycol/chemistry , Glycerol/chemistry , Glycine/chemistry , Air Pollutants/chemistry , Volatilization
3.
Angew Chem Int Ed Engl ; 51(11): 2767-71, 2012 Mar 12.
Article in English | MEDLINE | ID: mdl-22307737

ABSTRACT

Under the surface: Ag nanoparticles are deposited onto the surface of commercially available SiO particles, and subsequent chemical etching results in the formation of nanoporous SiO without changing the chemical and physical properties of the original SiO. Moreover, chemical-assisted thermal annealing produces a shape-preserving Si-based multicomponent system, which exhibits high-performance electrochemical properties.

6.
Nano Lett ; 9(11): 3844-7, 2009 Nov.
Article in English | MEDLINE | ID: mdl-19746961

ABSTRACT

We present Si nanotubes prepared by reductive decomposition of a silicon precursor in an alumina template and etching. These nanotubes show impressive results, which shows very high reversible charge capacity of 3247 mA h/g with Coulombic efficiency of 89%, and also demonstrate superior capacity retention even at 5C rate (=15 A/g). Furthermore, the capacity in a Li-ion full cell consisting of a cathode of LiCoO2 and anode of Si nanotubes demonstrates a 10 times higher capacity than commercially available graphite even after 200 cycles.

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