کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6890993 | 1445222 | 2018 | 44 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Learning-based classification of informative laryngoscopic frames
ترجمه فارسی عنوان
طبقه بندی مبتنی بر یادگیری از قاب های لارنگوسکوپی اطلاعاتی
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کلمات کلیدی
لارنکس، اندوسکوپی، انتخاب قاب، طبقه بندی تحت نظارت،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
چکیده انگلیسی
Background and Objective:
Early-stage diagnosis of laryngeal cancer is of primary importance to reduce patient morbidity. Narrow-band imaging (NBI) endoscopy is commonly used for screening purposes, reducing the risks linked to a biopsy but at the cost of some drawbacks, such as large amount of data to review to make the diagnosis. The purpose of this paper is to present a strategy to perform automatic selection of informative endoscopic video frames, which can reduce the amount of data to process and potentially increase diagnosis performance. Methods: A new method to classify NBI endoscopic frames based on intensity, keypoint and image spatial content features is proposed. Support vector machines with the radial basis function and the one-versus-one scheme are used to classify frames as informative, blurred, with saliva or specular reflections, or underexposed. Results: When tested on a balanced set of 720 images from 18 different laryngoscopic videos, a classification recall of 91% was achieved for informative frames, significantly overcoming three state of the art methods (Wilcoxon rank-signed test, significance level = 0.05). Conclusions: Due to the high performance in identifying informative frames, the approach is a valuable tool to perform informative frame selection, which can be potentially applied in different fields, such us computer-assisted diagnosis and endoscopic view expansion.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods and Programs in Biomedicine - Volume 158, May 2018, Pages 21-30
Journal: Computer Methods and Programs in Biomedicine - Volume 158, May 2018, Pages 21-30
نویسندگان
Sara Moccia, Gabriele O. Vanone, Elena De Momi, Andrea Laborai, Luca Guastini, Giorgio Peretti, Leonardo S. Mattos,