A retrieving system based on contents of fluoroscopic images, comprising: an image content feature extracting module, configured to perform feature extraction for contents of the fluoroscopic images; an image representing module, configured to construct an image representation; a retrieving module, configured to retrieve, based on a retrieval model, a plurality of images whose image representations have a higher similarity to an image representation under retrieval, and thereby construct a result of preliminary candidates; a feedback regulating module, configured to receive information feedback on the retrieval result from a user, and update the retrieval model; and an interacting module, configured to display the retrieval result, and collect feedback on user's satisfaction of the retrieval result, characterized in that the retrieving system comprises: a pre-classifying module configured to pre-classify fluoroscopic images and to classify the fluoroscopic images into texture images and non-texture images; and a diversified filtering module configured to construct a diversified retrieval result by filtering the result of preliminary candidates, using an SVM structural model, to select as the retrieval result an image subset capable of maximally covering a plurality of article categories; and in that the image content feature extracting module is configured to obtain feature vectors of the contents of fluoroscopic images by: with respect to a texture image, establishing an image pyramid, building super-pixel layer by layer, and establishing a texture description vector for every super-pixel, and with respect to a non-texture image, establishing an image pyramid, performing feature point detection pixel by pixel and layer by layer, and establishing a feature description vector for a detected feature point; and in that the image representing module is configured to combine feature description vectors of a same image to construct an image representation vector as said image representation. an image content feature extracting module, configured to perform feature extraction for contents of the fluoroscopic images; an image representing module, configured to construct an image representation; a retrieving module, configured to retrieve, based on a retrieval model, a plurality of images whose image representations have a higher similarity to an image representation under retrieval, and thereby construct a result of preliminary candidates; a feedback regulating module, configured to receive information feedback on the retrieval result from a user, and update the retrieval model; and an interacting module, configured to display the retrieval result, and collect feedback on user's satisfaction of the retrieval result, characterized in that the retrieving system comprises: a pre-classifying module configured to pre-classify fluoroscopic images and to classify the fluoroscopic images into texture images and non-texture images; and a diversified filtering module configured to construct a diversified retrieval result by filtering the result of preliminary candidates, using an SVM structural model, to select as the retrieval result an image subset capable of maximally covering a plurality of article categories; a pre-classifying module configured to pre-classify fluoroscopic images and to classify the fluoroscopic images into texture images and non-texture images; and a diversified filtering module configured to construct a diversified retrieval result by filtering the result of preliminary candidates, using an SVM structural model, to select as the retrieval result an image subset capable of maximally covering a plurality of article categories; and in that the image content feature extracting module is configured to obtain feature vectors of the contents of fluoroscopic images by: with respect to a texture image, establishing an image pyramid, building super-pixel layer by layer, and establishing a texture description vector for every super-pixel, and with respect to a non-texture image, establishing an image pyramid, performing feature point detection pixel by pixel and layer by layer, and establishing a feature description vector for a detected feature point; with respect to a texture image, establishing an image pyramid, building super-pixel layer by layer, and establishing a texture description vector for every super-pixel, and with respect to a non-texture image, establishing an image pyramid, performing feature point detection pixel by pixel and layer by layer, and establishing a feature description vector for a detected feature point; and in that the image representing module is configured to combine feature description vectors of a same image to construct an image representation vector as said image representation.