Method and apparatus for automatically identifying a region of interest in three-dimensional CT image

Abstract

The present invention discloses a method and an apparatus for automatically identifying a region of interest in a three-dimensional CT image. The method includes: training a 3D convolution neural network through a three-dimensional CT image marked with a region of interest to obtain a 3D convolutional neural network with a high identification rate for the region of interest; then, through the trained 3D convolution neural network, identifying the obtained three-dimensional CT image and obtaining the region of interest; and calculating the volume, the expansion direction and the expansion diameter of the interest of interest. With the method of the embodiments in the invention, the region of interest representing the lesion can be obtained automatically and efficiently, and the identifying accuracy is also higher. In addition, the volume, the expansion direction and the expansion diameter of the lesion can be automatically calculated, therefore, helping the doctor to make a more accurate judgment of the condition of a patient.

Description

technical field [0001] The invention relates to the field of medical image processing, in particular to a method and device for identifying a region of interest in a three-dimensional CT image. Background technique [0002] With the development of digital medical technology, the role of medical images in the medical diagnosis process has become more and more obvious, and it has gradually become the main tool for doctors to observe human lesions. When diagnosing a disease, doctors generally search for regions of interest representing lesions from medical images artificially based on experience. [0003] CT image is one of the most commonly used medical images. CT (full name in English: Computed Tomography, full name in Chinese: computerized tomography) images use precise and straight x-ray beams, gamma rays, ultrasound, etc., and are surrounded by highly sensitive detectors. In a certain part of the human body, it is obtained as one-by-one cross-sectional scanning. Although...

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