基于统计的高光谱皮肤数据处理分类方法

Beatriz Martínez-Vega, E. Quevedo, Raquel León, H. Fabelo, S. Ortega, G. Callicó, Irene Castaño, G. Carretero, P. Almeida, Aday García, Javier A. Hernández, Stig Uteng, F. Godtliebsen
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摘要

用于皮肤病学应用的高光谱成像(HSI)缺乏区分癌性或非癌性色素皮肤病变的物理模型。在本文中,一组恒生指数数据的统计特性被利用作为这种限制的替代方案。实验中使用的高光谱皮肤病学数据库由来自61例患者的40个非癌性和36个癌性色素皮肤病变(psl)组成。初步的实验表明,一个简单的统计指标,如变异系数,利用高光谱数据来区分癌性和非癌性psl的潜力。在测试集中实现了100%的灵敏度结果,提供了80%的总体准确率分类。
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Statistics-based Classification Approach for Hyperspectral Dermatologic Data Processing
Hyperspectral Imaging (HSI) for dermatology applications lacks a physical model to differentiate between cancerous or non-cancerous pigmented skin lesions. In this paper the statistical properties of a set of HSI data are exploited as an alternative to this limitation. The hyperspectral dermatologic database employed in the experiments is composed by 40 noncancerous and 36 cancerous pigmented skin lesions (PSLs) obtained from 61 patients. The preliminary experiments suggest the potential of a simple statistics metrics, such as the coefficient of variation, to distinguish between cancerous and non-cancerous PSLs using hyperspectral data. A sensitivity result of 100% was achieved in the test set providing an overall accuracy classification of 80%.
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