The present application related to a method for detecting image using hyperspectral imaging by band selection. Firstly, obtaining a hyperspectral imaging information according to a reference image, hereby, obtaining corresponded hyperspectral image from an input image, and obtaining corresponded feature values by band selection for operating Principal components analysis to simplify feature values. Then, obtaining feature images by Convolution kernel, and then positioning an image of an object under detected by a default box and a boundary box from the feature image. By Comparing with the esophageal cancer sample image, the image of the object under detected is classifying to an esophageal cancer image or a non-esophageal cancer image. Thus, detecting an input image from the image capturing device by the convolutional neural network to judge if the input image is the esophageal cancer image for helping the doctor to interpret the image of the object under detected.

A system and method are presented for use in angiographic imaging. The system comprises: a light source unit, and at least one imaging unit comprising a detector array, wherein the detector array comprises at least first and second types of detector cells having corresponding first and second different spectral response functions defining respectively first and second spectral peaks; and the light source is unit configured for emitting light formed of at least first and second discrete wavelength ranges which are selected to be aligned with said first and second spectral peaks of said first and second types of detector cells.