The Experts below are selected from a list of 252 Experts worldwide ranked by ideXlab platform
Huw Smith - One of the best experts on this subject based on the ideXlab platform.
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Machine vision application to the detection of water-borne Micro-Organisms
Intelligent Decision Technologies, 2009Co-Authors: Hernando Fernandez-canque, Sorin Hintea, Gabor Csipkes, Sorin Bota, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. The machine vision proposed provides a 100% detection of cryptosporidium Micro-Organism as test case. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
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machine vision application to the detection of micro organism in drinking water
International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, 2008Co-Authors: Hernando Fernandezcanque, Sorin Hintea, Gabor Csipkes, Allan Pellow, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
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KES (3) - Machine Vision Application to the Detection of Micro-Organism in Drinking Water
Lecture Notes in Computer Science, 1Co-Authors: Hernando Fernandez-canque, Sorin Hintea, Gabor Csipkes, Allan Pellow, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
Hernando Fernandez-canque - One of the best experts on this subject based on the ideXlab platform.
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Machine vision application to the detection of water-borne Micro-Organisms
Intelligent Decision Technologies, 2009Co-Authors: Hernando Fernandez-canque, Sorin Hintea, Gabor Csipkes, Sorin Bota, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. The machine vision proposed provides a 100% detection of cryptosporidium Micro-Organism as test case. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
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KES (3) - Machine Vision Application to the Detection of Micro-Organism in Drinking Water
Lecture Notes in Computer Science, 1Co-Authors: Hernando Fernandez-canque, Sorin Hintea, Gabor Csipkes, Allan Pellow, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
Shaili Gupta - One of the best experts on this subject based on the ideXlab platform.
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Parvimonas micra: A rare cause of native joint septic arthritis
Anaerobe, 2016Co-Authors: Adam Baghban, Shaili GuptaAbstract:Parvimonas micra is a fastidious, anaerobic, gram positive coccus, which is found in normal human oral and gastrointestinal flora. It has also been known as Peptostreptococcus micros and Micromonas micros with its most recent re-classification in 2006. It has been described in association with hematogenous seeding of prosthetic joints [1,2]. Several cases of discitis and osteomyelitis have been described in association with dental procedures and periodontal disease often with a subacute presentation. However, cases of native joint septic arthritis are limited [3-5]. Per our literature review, there is one case of native knee septic arthritis described in 1999, with a prolonged time to diagnosis and treatment due to difficulty culturing P. micra. The previously reported patient experienced significant joint destruction and morbidity [6]. Advances in culture techniques and new methods of organism identification including MALDI-TOF and 16s rRNA sequencing have lead to increased identification of this organism, which may be a more frequent bone and joint pathogen than previously realized.
Sorin Hintea - One of the best experts on this subject based on the ideXlab platform.
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Machine vision application to the detection of water-borne Micro-Organisms
Intelligent Decision Technologies, 2009Co-Authors: Hernando Fernandez-canque, Sorin Hintea, Gabor Csipkes, Sorin Bota, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. The machine vision proposed provides a 100% detection of cryptosporidium Micro-Organism as test case. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
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machine vision application to the detection of micro organism in drinking water
International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, 2008Co-Authors: Hernando Fernandezcanque, Sorin Hintea, Gabor Csipkes, Allan Pellow, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
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KES (3) - Machine Vision Application to the Detection of Micro-Organism in Drinking Water
Lecture Notes in Computer Science, 1Co-Authors: Hernando Fernandez-canque, Sorin Hintea, Gabor Csipkes, Allan Pellow, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
Gabor Csipkes - One of the best experts on this subject based on the ideXlab platform.
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Machine vision application to the detection of water-borne Micro-Organisms
Intelligent Decision Technologies, 2009Co-Authors: Hernando Fernandez-canque, Sorin Hintea, Gabor Csipkes, Sorin Bota, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. The machine vision proposed provides a 100% detection of cryptosporidium Micro-Organism as test case. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
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machine vision application to the detection of micro organism in drinking water
International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, 2008Co-Authors: Hernando Fernandezcanque, Sorin Hintea, Gabor Csipkes, Allan Pellow, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.
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KES (3) - Machine Vision Application to the Detection of Micro-Organism in Drinking Water
Lecture Notes in Computer Science, 1Co-Authors: Hernando Fernandez-canque, Sorin Hintea, Gabor Csipkes, Allan Pellow, Huw SmithAbstract:The work presented in this paper uses a novel Machine Vision application to detect and identify Micro-Organism oocysts on drinking water. This new concept of water borne Micro-Organism detection uses image processing to allow detailed inspection of parasite morphology to nanometre dimensions. The detection results are more reliable than existing manual methods. Combining Normarski Differential Interface Contrast (DIC) and fluorescence microscopy using Fluorescein Isothiocyanate (FITC) and UV filters, the system provides a reliable detection of Micro-Organisms with a considerable reduction in time, cost and subjectivity over the current labour intensive time consuming manual method.