小波
小波变换
阈值
人工智能
模式识别(心理学)
胶质瘤
计算机科学
小波包分解
计算机视觉
数学
图像(数学)
医学
癌症研究
作者
Irina N. Dolganova,P. V. Aleksandrova,S.-I. T. Beshplav,Nikita V. Chernomyrdin,Evgeniya N. Dubyanskaya,S A Goryaynov,V. N. Kurlov,Igor V. Reshetov,A A Potapov,Valery V. Tuchin,Kirill I. Zaytsev
摘要
We have proposed a wavelet-domain de-noising technique for imaging of human brain malignant glioma by optical coherence tomography (OCT). It implies OCT image decomposition using the direct fast wavelet transform, thresholding of the obtained wavelet spectrum and further inverse fast wavelet transform for image reconstruction. By selecting both wavelet basis and thresholding procedure, we have found an optimal wavelet filter, which application improves differentiation of the considered brain tissue classes – i.e. malignant glioma and normal/intact tissue. Namely, it allows reducing the scattering noise in the OCT images and retaining signal decrement for each tissue class. Therefore, the observed results reveals the wavelet-domain de-noising as a prospective tool for improved characterization of biological tissue using the OCT.
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