Development of manifold learning based texture analysis for lesions within noise included medical images

点击翻译按钮获取中文摘要

Manifold learning based image analyses for detecting lesion in medical images were studied experimentally. Various medical images are noisy in common, because imaging conditions and parameters are fixed for reduction of patients’ burdens. However some experimental validation showed the noise included medical images has only a limited effect on learning low-dimensional manifold of voxel-wise texture feature space and voxel classification by the texture features. In addition, the benefit of the cascade classification by a manifold based one class classifier and a two class classifier was shown through experiments of the GGO voxel classification and the GGO nodule region detection.