Case database diagnosis system based on four-modal medical imaging

Abstract

The invention provides a case database diagnosis system based on four-modal medical images, including: CT image equipment, PET image equipment, SPET image equipment, FMI image equipment, image acquisition module, network communication module and terminal processor, image acquisition module The input terminals are respectively connected to CT imaging equipment, PET imaging equipment, SPET imaging equipment, and FMI imaging equipment, and the output terminals are connected to the network communication module. The image acquisition module collects four-mode medical images, and encapsulates the four-channel image signals into a video stream for transmission. To the network communication module, the network communication module is respectively connected with the image acquisition module and the terminal processor to send the received video stream to the terminal processor, and the terminal processor diagnoses the disease by detecting the similarity between the medical image and the feature library And build a case library. The invention has the advantages of high accuracy, low rates of misdiagnosis and missed diagnosis, can establish a complete case library system, and has broad application prospects.

Description

technical field [0001] The invention relates to the technical field of medical image diagnosis, in particular to a case database diagnosis system based on four-modal medical images. Background technique [0002] CT and PET images are an important basis for diagnosing patients' diseases. Since CT and PET examinations usually examine the whole body of a patient, the amount of image data obtained is large. At present, for the completed CT and PET images, the doctor directly observes the disease with the naked eye. When the doctor makes the diagnosis, due to the large amount of image data and the limited ability of the human eye to recognize the image, it is inevitable that there will be There are various situations such as misdiagnosis and missed diagnosis, which have left great hidden dangers to the accuracy of patient treatment. In addition, the existing pathological feature database only includes disease conditions and pathological image features manually marked by medical ...

AI Technical Summary

Problems solved by technology

At present, for the completed CT and PET images, the doctor directly observes the disease with the naked eye. When the doctor makes the diagnosis, due to the large amount of image data and the limited ability of the human eye to recognize the image, it is inevitable that there will be Various situations such as misdiagnosis and missed diagnosis have left great hidden dangers to the accuracy of patient treatment.

In addition, the existing pathological feature database only includes disease conditions and pathological image features manually marked by medical experts on cases with obvious relevant characteristics to assist doctors in diagnosis. The case database has a single form, incomplete information, and cannot be updated in time. The cycle is long, resulting in low efficiency of case database auxiliary diagnosis

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