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  1. Article ; Online: Automated detection of actinic keratoses in clinical photographs.

    Samuel C Hames / Sudipta Sinnya / Jean-Marie Tan / Conrad Morze / Azadeh Sahebian / H Peter Soyer / Tarl W Prow

    PLoS ONE, Vol 10, Iss 1, p e

    2015  Volume 0112447

    Abstract: BACKGROUND:Clinical diagnosis of actinic keratosis is known to have intra- and inter-observer variability, and there is currently no non-invasive and objective measure to diagnose these lesions. OBJECTIVE:The aim of this pilot study was to determine if ... ...

    Abstract BACKGROUND:Clinical diagnosis of actinic keratosis is known to have intra- and inter-observer variability, and there is currently no non-invasive and objective measure to diagnose these lesions. OBJECTIVE:The aim of this pilot study was to determine if automatically detecting and circumscribing actinic keratoses in clinical photographs is feasible. METHODS:Photographs of the face and dorsal forearms were acquired in 20 volunteers from two groups: the first with at least on actinic keratosis present on the face and each arm, the second with no actinic keratoses. The photographs were automatically analysed using colour space transforms and morphological features to detect erythema. The automated output was compared with a senior consultant dermatologist's assessment of the photographs, including the intra-observer variability. Performance was assessed by the correlation between total lesions detected by automated method and dermatologist, and whether the individual lesions detected were in the same location as the dermatologist identified lesions. Additionally, the ability to limit false positives was assessed by automatic assessment of the photographs from the no actinic keratosis group in comparison to the high actinic keratosis group. RESULTS:The correlation between the automatic and dermatologist counts was 0.62 on the face and 0.51 on the arms, compared to the dermatologist's intra-observer variation of 0.83 and 0.93 for the same. Sensitivity of automatic detection was 39.5% on the face, 53.1% on the arms. Positive predictive values were 13.9% on the face and 39.8% on the arms. Significantly more lesions (p<0.0001) were detected in the high actinic keratosis group compared to the no actinic keratosis group. CONCLUSIONS:The proposed method was inferior to assessment by the dermatologist in terms of sensitivity and positive predictive value. However, this pilot study used only a single simple feature and was still able to achieve sensitivity of detection of 53.1% on the arms.This suggests that image analysis ...
    Keywords Medicine ; R ; Science ; Q
    Subject code 630
    Language English
    Publishing date 2015-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: RNA-seq reveals more consistent reference genes for gene expression studies in human non-melanoma skin cancers

    Van L.T. Hoang / Lisa N. Tom / Xiu-Cheng Quek / Jean-Marie Tan / Elizabeth J. Payne / Lynlee L. Lin / Sudipta Sinnya / Anthony P. Raphael / Duncan Lambie / Ian H. Frazer / Marcel E. Dinger / H. Peter Soyer / Tarl W. Prow

    PeerJ, Vol 5, p e

    2017  Volume 3631

    Abstract: Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a ... ...

    Abstract Identification of appropriate reference genes (RGs) is critical to accurate data interpretation in quantitative real-time PCR (qPCR) experiments. In this study, we have utilised next generation RNA sequencing (RNA-seq) to analyse the transcriptome of a panel of non-melanoma skin cancer lesions, identifying genes that are consistently expressed across all samples. Genes encoding ribosomal proteins were amongst the most stable in this dataset. Validation of this RNA-seq data was examined using qPCR to confirm the suitability of a set of highly stable genes for use as qPCR RGs. These genes will provide a valuable resource for the normalisation of qPCR data for the analysis of non-melanoma skin cancer.
    Keywords RNA-seq ; Reference gene ; qPCR ; Non-melanoma skin cancer ; Medicine ; R ; Biology (General) ; QH301-705.5
    Language English
    Publishing date 2017-08-01T00:00:00Z
    Publisher PeerJ Inc.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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