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Aribisala, Benjamin:

Computing Irregularity for Features in Medical Images - A Case Study of Malignant Melanoma, a skin cancer - Taschenbuch

2010, ISBN: 9783838387635

[ED: Taschenbuch / Paperback], [PU: LAP Lambert Academic Publishing], The irregularity of a lesion border has been identified as the most significant factor in the diagnosis of malignant … Mehr…

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Computing Irregularity for Features in Medical Images - Taschenbuch

2010, ISBN: 9783838387635

The irregularity of a lesion border has been identified as the most significant factor in the diagnosis of malignant melanoma. The objective of the research was to find objective computab… Mehr…

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Computing Irregularity for Features in Medical Images
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Computing Irregularity for Features in Medical Images - neues Buch

ISBN: 9783838387635

The irregularity of a lesion border has been identified as the most significant factor in the diagnosis of malignant melanoma. The objective of the research was to find objective computab… Mehr…

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Computing Irregularity for Features in Medical Images - neues Buch

ISBN: 9783838387635

The irregularity of a lesion border has been identified as the most significant factor in the diagnosis of malignant melanoma. The objective of the research was to find objective computab… Mehr…

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Aribisala, Benjamin:
Computing Irregularity for Features in Medical Images - Taschenbuch

2010, ISBN: 9783838387635

Erscheinungsdatum: 07/2010, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Computing Irregularity for Features in Medical Images, Titelzusatz: A Case Study of Malignant Mel… Mehr…

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Computing Irregularity for Features in Medical Images

The irregularity of a lesion border has been identified as the most significant factor in the diagnosis of malignant melanoma. The objective of the research was to find objective computable measures of contour irregularity and to apply them to skin lesions. A descriptive definition of irregularity was formulated which defines irregularity in terms of the five attributes: departure from a typical sequence (deviation), lack of obvious description, lack of compressibility, lack of symmetry and lack of a rule for generating a sequence. Methods based on the Hidden Markov Models, the Conditional Entropy, and a novel method based on Pattern Theory, were implemented, evaluated and tested. Their predictive power as classifiers of lesion abnormality was tested on 98 lesions. All methods showed sensitivity and specificity of over 0.7, with 0.82 scored for the Weibull based Hidden Markov Models. Ranking correlation between the computed measures and the human perception of the border irregularity varied from W=0.49 for the Hidden Markov Models based measure to W=0.95 for the measure based on Pattern Theory.

Detailangaben zum Buch - Computing Irregularity for Features in Medical Images


EAN (ISBN-13): 9783838387635
ISBN (ISBN-10): 3838387635
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2010
Herausgeber: LAP Lambert Acad. Publ.
228 Seiten
Gewicht: 0,356 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2008-07-31T07:58:20+02:00 (Vienna)
Detailseite zuletzt geändert am 2020-01-25T11:22:50+01:00 (Vienna)
ISBN/EAN: 3838387635

ISBN - alternative Schreibweisen:
3-8383-8763-5, 978-3-8383-8763-5
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: benjamin
Titel des Buches: doing images


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