Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears - Wikidata - awgldk - TriplyDB

Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

http://www.wikidata.org/entity/Q33499581

about

Morphological characterization of Mycobacterium tuberculosis in a MODS culture for an automatic diagnostics through pattern recognition Creating a virtual slide map from sputum smear images for region-of-interest localisation in automated microscopy Clinical microbiology informatics.A review of cellphone microscopy for disease detection.A Low Cost/Low Power Open Source Sensor System for Automated Tuberculosis Drug Susceptibility Testing.A Review of Automatic Methods Based on Image Processing Techniques for Tuberculosis Detection from Microscopic Sputum Smear Images.Automated focusing in bright-field microscopy for tuberculosis detection.Automatic microscopic detection of mycobacteria in sputum: a proof-of-concept Automated tuberculosis diagnosis using fluorescence images from a mobile microscope

P2860

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P2860

Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

http://www.wikidata.org/entity/Q33499581

description

2009 nî lūn-bûn

@nan

2009 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած

@hyw

2009 թվականի սեպտեմբերին հրատարակված գիտական հոդված

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2009年の論文

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2009年論文

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2009年論文

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2009年論文

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2009年論文

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2009年論文

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2009年论文

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name

Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

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Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

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type

label

Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

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Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

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prefLabel

Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

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Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

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TITB.2009.2028339

P1433

IEEE Transactions on Information Technology in Biomedicine

P1476

Classification of Mycobacterium tuberculosis in images of ZN-stained sputum smears

@en

P2093

Andrew Whitelaw

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Genevieve Learmonth

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Konstantinos Veropoulos

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Rethabile Khutlang

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Sriram Krishnan

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P2860

Fluorescence versus conventional sputum smear microscopy for tuberculosis: a systematic review.

Automated detection of tuberculosis in Ziehl-Neelsen-stained sputum smears using two one-class classifiers

Image processing techniques for identifying Mycobacterium tuberculosis in Ziehl-Neelsen stains.

The future looks bright: low-cost fluorescent microscopes for detection of Mycobacterium tuberculosis and Coccidiae.

Optimal tuberculosis case detection by direct sputum smear microscopy: how much better is more?

Improved sensitivity of sputum smear microscopy after processing specimens with C18-carboxypropylbetaine to detect acid-fast bacilli: a study of United States-bound immigrants from Vietnam.

Automatic detection of unstained viable cells in bright field images using a support vector machine with an improved training procedure.

Fast branch & bound algorithms for optimal feature selection.

Automated identification of tubercle bacilli in sputum. A preliminary investigation.

A methodology for evaluation of boundary detection algorithms on medical images.

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scholarly article

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10.1109/TITB.2009.2028339

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4

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14

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Tania S. Douglas

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2009-09-01T00:00:00Z

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220521347

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19726269

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P921

Mycobacterium tuberculosis

P932

2953636

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