Rib fracture image detection method based on small sample deep learning

A deep learning and rib fracture technology, applied in the field of rib fracture image detection, can solve the unseen problems of deep learning in rib fracture detection and achieve the effect of reducing demand

Pending Publication Date: 2021-03-16
NEIJIANG NORMAL UNIV
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Problems solved by technology

[0007] However, there is no application of deep learning in rib fracture detection in the above research results

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  • Rib fracture image detection method based on small sample deep learning
  • Rib fracture image detection method based on small sample deep learning
  • Rib fracture image detection method based on small sample deep learning

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Embodiment Construction

[0020] Slight rib fractures are easy to be ignored. To solve this problem, the present invention proposes a deep learning model for image detection of rib fractures based on the YOLO-v3 model and using transfer learning methods to process small samples. This method uses a small amount of labeled rib CT images as the data of the input layer, performs transfer learning based on the fine-tuned Yolo-v3 model, and finally conducts deep learning training. The model needs to deal with fewer samples and has a wider range of applications in practice. The final experiment shows that the method requires fewer iterations and obtains high accuracy, thereby improving the accuracy of rib fracture image detection and providing a good basis for doctors' diagnosis.

[0021] Below in conjunction with accompanying drawing, the method of the present invention is described in detail as follows:

[0022] Such as figure 1 As shown, a rib fracture image detection method based on small-sample deep le...

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Abstract

The invention discloses a rib fracture image detection method based on small sample deep learning. The method comprises the following steps: step 1, marking a collected rib fracture CT image; 2, performing feature extraction by adopting a YOLOv3 model; 3, carrying out transfer learning on the extracted feature vectors; and 4, carrying out deep learning training. Compared with the prior art, the method has the positive effects that a YOLOv3 model is provided, small samples are processed by means of a transfer learning method, and a deep learning model for rib fracture image detection is established. According to the method, few rib CT images are used as data of an input layer for deep learning training, the obtained effective rate is high, and therefore a small sample deep learning model can be established, and a good basis is provided for diagnosis of doctors.

Description

technical field [0001] The invention discloses a rib fracture image detection method based on small-sample deep learning. Background technique [0002] Rib fracture is one of the common traumas, and its diagnosis mainly depends on imaging examination. Clinical imaging methods for rib fractures mainly include DR examination and multi-slice spiral CT examination. DR is currently the preferred method for the examination of chest injuries. It is widely used in the routine examination of rib fractures due to its low cost, simple operation, and low radiation dose. The missed diagnosis rate is high. Multi-slice spiral CT transverse or oblique scanning is also applied to the diagnosis of rib fractures. However, due to the large number of ribs and the irregular shape, CT examination has defects such as inaccurate counting and limited scope. The 2D and 3D reconstructions of SCT and MSCT have been widely used in the diagnosis of bone diseases, including the diagnosis of rib fractur...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06N3/08G06T2207/20081G06T2207/20084G06T2207/10081G06T2207/30008G06V2201/03G06N3/045G06F18/253
Inventor 李甫孔花吴开腾陈泓杏余文春张莉周丹李季
Owner NEIJIANG NORMAL UNIV
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