Evaluation of Preprocessing Methods on Independent Medical Hyperspectral Databases to Improve Analysis.

ABSTRACT: Currently, one of the most common causes of death worldwide is cancer. The development of innovative methods to support the early and accurate detection of cancers is required to increase the recovery rate of patients. Several studies have shown that medical Hyperspectral Imaging (HSI) combined with artificial intelligence algorithms is a powerful tool for cancer detection. Various preprocessing methods are commonly applied to hyperspectral data to improve the performance of the algorithms. However, there is currently no standard for these methods, and no studies have compared them so far in the medical field. In this work, we evaluated different combinations of preprocessing steps, including spatial and spectral smoothing, Min-Max scaling, Standard Normal Variate normalization, and a medi

SUBMITTER: Martinez-Vega B 

PROVIDER: S-EPMC9693077 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature