An Effective Occipitomental View Enhancement Based on Adaptive Morphological Texture Analysis

作者：Chondro Peter^*; Hu Hao Chun; Hung Hsuan Yen; Chang Shin Yuan; Li Lieber Po Hung; Ruan Shanq Jang

来源：IEEE Journal of Biomedical and Health Informatics, 2017, 21(4): 1105-1113.

DOI：10.1109/JBHI.2016.2593455

• Diagnosis apparatus
• maxillary sinusitis
• occipitomental view
• radiography enhancement
• texture analysis

This paper aims to present an algorithm that specifically enhances maxillary sinuses using a novel contrast enhancement technique based on the adaptive morphological texture analysis for occipitomental view radiographs. First, the skull X-ray (SXR) is decomposed into rotational blocks (RBs). Second, each RB is rotated into various directions and processed using morphological kernels to obtain the dark and bright features. Third, a gradient-based block segmentation decomposes the interpolated feature maps into feature blocks (FBs). Finally, the histograms of FBs are equalized and overlaid locally to the input SXR. The performance of the proposed method was evaluated on an independent dataset, which comprises of 145 occipitomental view-based human SXR images. According to the experimental results, the proposed method is able to increase the diagnosis accuracy by 83.45% compared with the computed tomography modality as the gold standard.

• 出版日期2017-7