A medical image bone segmentation method based on the combination of pspnet and hed

A medical image and combined technology, applied in the field of medical image bone segmentation, can solve the problems of only focusing on pixel grayscale features, not fully considering the spatial characteristics, and the effect of noise images is not ideal, so as to improve the segmentation effect and measure various performances. Value boost effect

Active Publication Date: 2022-02-11
XINGAOYI MEDICAL EQUIP CO LTD
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Problems solved by technology

However, this method does not fully consider the spatial characteristics, and only focuses on the grayscale features of pixels, which is not ideal for noisy images.

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  • A medical image bone segmentation method based on the combination of pspnet and hed
  • A medical image bone segmentation method based on the combination of pspnet and hed
  • A medical image bone segmentation method based on the combination of pspnet and hed

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Embodiment Construction

[0021] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0022] Such as figure 1 As shown in (a), PSPNet uses the pre-trained ResNet model to generate the initial feature map, then integrates the context information through the pyramid pooling module, uses the four-layer pyramid structure to obtain global features, and then combines the global features with the original The feature maps are concatenated and passed through convolutional layers to generate the final prediction map.

[0023] Such as figure 1 As shown in (b), HED adds five side output lay...

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Abstract

The invention discloses a medical image bone segmentation method based on the combination of PSPNet and HED, combining PSPNet and HED to form a new network structure, using limited medical images for training, and identifying ribs and spine in chest images extract. The invention uses a novel neural network structure and realizes bone segmentation of complex medical images.

Description

technical field [0001] The invention relates to a medical image bone segmentation method based on the combination of PSPNet and HED, belonging to the field of computer image processing. Background technique [0002] At present, traditional medical image segmentation methods mainly include threshold-based feature segmentation and region-based feature segmentation. Threshold segmentation is the most common segmentation method for directly detecting target regions, and threshold segmentation can be divided into single-threshold segmentation and multi-threshold segmentation. Single-threshold segmentation only needs to select a threshold to divide the image into a background part and a target part. Multi-threshold segmentation needs to set multiple thresholds to segment the image into multiple target positions. In order to distinguish the targets obtained by different thresholds, each area needs to be mark. The effect of region segmentation depends on the selection of threshold...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11
CPCG06T7/11G06T2207/10081G06T2207/20016G06T2207/20081G06T2207/20084G06T2207/30008
Inventor 陈阳宋晓伟高大志陈吉瑞
Owner XINGAOYI MEDICAL EQUIP CO LTD
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