Image segmentation method and device, diagnosis system and storage medium

An image segmentation and image technology, applied in the computer field, can solve problems such as poor tumor image segmentation

Active Publication Date: 2019-04-09
TENCENT TECH (SHENZHEN) CO LTD +1
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  • Application Information

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Problems solved by technology

[0006] In order to solve the problem of poor tumor image segmentation in the related art, each embodiment of the present invention provides an image segmentation method, device, diagnostic system and storage medium

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  • Image segmentation method and device, diagnosis system and storage medium
  • Image segmentation method and device, diagnosis system and storage medium
  • Image segmentation method and device, diagnosis system and storage medium

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Embodiment Construction

[0036] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with aspects of the invention as recited in the appended claims.

[0037] As mentioned earlier, tumor image segmentation is mainly based on deep learning, including fully convolutional neural network methods and U-net-based network methods.

[0038] Among them, such as figure 1 As shown, the fully convolutional neural network method uses two parallel branches 101 and 103 to perform feature learning on images 1011 and 1031 of different sizes, and the larger-sized i...

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Abstract

The invention discloses an image segmentation method and device, a diagnosis system and a storage medium. The image segmentation method comprises the steps of obtaining a tumor image; Carrying out tumor positioning on the obtained tumor image to obtain a candidate image for indicating the position of a full tumor region in the tumor image; Inputting the candidate image into a cascade segmentationnetwork constructed based on a machine learning model; And carrying out image segmentation on the whole tumor region in the candidate image by using a first-stage segmentation network in the cascade segmentation network as a starting point, and stepping to a last-stage segmentation network step by step to carry out image segmentation on an enhanced tumor core region to obtain a segmented image. Byadopting the image segmentation method and device, the diagnosis system and the storage medium provided by the invention, the problem of poor tumor image segmentation effect in the prior art is solved.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to an image segmentation method, device, diagnosis system and storage medium. Background technique [0002] Glioma is the most common primary malignant brain tumor, also known as brain tumor, with varying degrees of invasiveness, and is often divided into whole tumor area, tumor core area, and enhanced tumor core area. [0003] Magnetic resonance imaging (Magnetic Resonance Imaging, MRI) is the most commonly used method for the examination and diagnosis of brain tumors in clinical practice. medical value. [0004] At present, tumor image segmentation is mainly based on deep learning, including fully convolutional neural network (FCNNS, Fully convolutional neural networks) method and U-net based network (U-net based network) method. [0005] However, the inventors have found that the features learned by the full convolutional neural network method are based on the local p...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11G06N99/00
CPCG06T7/11G06T2207/20081G06T2207/30096G06T2207/20084G06T2207/30016G06T2207/10081G06T2207/10088G06N3/084G06V30/2504G06V2201/031G06V10/806G06N7/01G06N3/045G06F18/253G06N20/00G06T7/0012
Inventor 胡一凡郑冶枫
Owner TENCENT TECH (SHENZHEN) CO LTD
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