Capsule endoscope image retrieval method based on wavelet transformation

Abstract

The invention discloses a capsule endoscope image retrieval method based on wavelet transformation. The method comprises the following steps: constructing an image database including standard pathological images and images to be retrieved; transforming the color spaces of the standard pathological images and the images to be retrieved in the image database to the HSI (hue, saturation, intensity) form; extracting the low-frequency waveband information from each HIS component of the processed image, and calculating the feature similarity between the processed standard pathological images and each image to be retrieved by use of Euclidean distance; and selecting the image to be retrieved with low feature similarity as the suspected pathological image. The method is used for processing the capsule endoscope images, and can retrieve the abnormal images from the images to be retrieved by comparing the capsule endoscope images with the pathological images, thereby reducing the labor intensity of film reading doctors and improving the diagnosis efficiency.

Description

technical field [0001] The invention relates to a medical image processing method, in particular to a capsule endoscope image retrieval method based on wavelet transform. Background technique [0002] In 2001, the world's first capsule endoscopy system was approved by the US FDA for clinical application. By the end of 2010, more than 1 million people in the world have received capsule endoscopy. Because capsule endoscopy is painless and can be observed from the mouth to the anus Therefore, it has become an important inspection method for the diagnosis of digestive tract diseases. However, the image volume of capsule endoscopy is huge. Calculated by taking two pictures per second, the number of pictures produced during the 6-8 hour inspection process reaches 43,200-57,600 pictures, all these pictures are carefully interpreted one by one by the doctor to make the correct diagnosis. The workload of reading the pictures is huge, it takes a lot of time, and it is easy to get tire...

AI Technical Summary

Problems solved by technology

[0002] In 2001, the world's first capsule endoscopy system was approved by the US FDA for clinical application. By the end of 2010, more than 1 million people in the world have received capsule endoscopy. Because capsule endoscopy is painless and can be observed from the mouth to the anus Therefore, it has become an important inspection method for the diagnosis of digestive tract diseases. However, the image volume of capsule endoscopy is huge. Calculated by taking two pictures per second, the number of pictures produced during the 6-8 hour inspection process reaches 43,200-57,600 pictures, all these pictures are carefully interpreted one by one by the doctor to make the correct diagnosis. The workload of reading the pictures is huge, it takes a lot of time, and it is easy to get tired and miss valuable diagnostic information. The diagnostic efficiency is extremely low. It is difficult to cope with a large amount of inspection. Therefore, the manual interpretation of capsule endoscopic images has become a bottleneck restricting its development. It has important practical value with automatic analysis system

According to our preliminary research, although the lesions of the digestive tract are ever-changing, the features reflected on the endoscopic pictures are limited, such as bulge, depression, swelling, shrinkage, abnormal color, etc.

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