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Bone scanning image hotspot segmentation method and system, medium and equipment

A bone scan and image technology, applied in bone scan image hotspot segmentation, bone scan image hotspot segmentation based on conditional generative confrontation network and multi-instance learning, to achieve good segmentation accuracy

Active Publication Date: 2020-08-14
SHANGHAI JIAO TONG UNIV
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  • Claims
  • Application Information

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There is still room for improvement in the effect of bone scan image processing in this patent

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  • Bone scanning image hotspot segmentation method and system, medium and equipment
  • Bone scanning image hotspot segmentation method and system, medium and equipment
  • Bone scanning image hotspot segmentation method and system, medium and equipment

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Embodiment Construction

[0028] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to protection domain of the present invention.

[0029] like Figure 1-7 As shown, a bone scan image hotspot segmentation method according to the present invention includes: Step S1: using the pix2pix model in CGAN to divide the bone scan image into 4 regions according to the knowledge of human anatomy, thereby obtaining a 4-dimensional position Feature vector; step S2: combine 4-dimensional position feature, 33-dimensional texture feature, and 1-dimensional neighborhood contrast feature into artificial features of bone scan image; step S3: use CGAN to d...

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Abstract

The invention provides a bone scanning image hotspot segmentation method and system, a medium and equipment. The method comprises the steps: S1, obtaining a four-dimensional position feature vector; S2, combining the four-dimensional position feature, the 33-dimensional texture feature and the one-dimensional neighborhood contrast feature into an artificial feature of the bone scanning image; S3,constructing a 38-dimensional feature; S4, training a small block level classifier by using MIL to obtain a probability distribution diagram of the hot spots, and obtaining an initial contour similarto the segmentation target through threshold segmentation; and S5, obtaining a bone scanning image hotspot segmentation result by using level set evolution, and obtaining bone scanning image hotspot segmentation result information. The CGAN can be utilized to calculate the position features, and the position features, the texture features and the contrast features are combined into the artificialfeatures of the bone scanning image.

Description

technical field [0001] The present invention relates to the field of medical image segmentation, in particular, to a bone scan image hotspot segmentation method, system, medium and equipment, especially a bone scan image hotspot segmentation method based on conditional generative adversarial network and multi-instance learning. Background technique [0002] Hotspot segmentation of bone scan images is an essential means for clinical diagnosis of tumors and related bone diseases caused by them. When detected, the tumor was much brighter than other areas in the image and was called a "hot spot" in the study. In recent years, with the advancement of computer technology, the research on hot spot segmentation of bone scan images has achieved great development. [0003] In 2004, Yin et al. used local maxima to segment potential hotspots; in 2007, Huang et al. segmented bone scan images into 23 human body regions, and then established a linear regression analysis model through the ...

Claims

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Application Information

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IPC IPC(8): G06T7/11G06T7/136G06N3/04G06N3/08
CPCG06T7/11G06T7/136G06N3/08G06T2207/20024G06T2207/20081G06T2207/20084G06T2207/30008G06N3/044
Inventor 乔宇徐航
Owner SHANGHAI JIAO TONG UNIV
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