Femoral neck fracture detection method and system based on weakly supervised segmentation
A femoral neck fracture and weak supervision technology, which is applied in the field of medical image processing, can solve the problems of poor detection accuracy, low efficiency, femoral neck area detection, etc., and achieve the effect of fast efficiency and high detection accuracy
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Embodiment 1
[0075] The method for femoral neck fracture detection based on weakly supervised segmentation includes the following detection steps:
[0076] Acquire the detection image, input the acquired femoral neck X-ray film into the constructed and trained detection neural network to detect the femoral part, and obtain the probability segmentation map Pprobability and the femoral neck area detection image P detec ;
[0077] Obtain the fracture type of the femoral neck region, and detect the femoral region in the image P detec Input to the constructed and trained classification network to obtain the type of femoral fracture;
[0078] Obtain the segmented fracture site and detect the femur area in the image P detec Input the constructed and trained weakly supervised segmentation network to obtain the segmented fracture image Pseg;
[0079] The images of the femoral neck fracture area are obtained by image fusion, and the segmented fracture image Pseg is combined with the femoral area ...
Embodiment 2
[0124] On the basis of Embodiment 1, the system for femoral neck fracture detection based on weakly supervised segmentation in this embodiment includes a detection module, a classification module, a weakly supervised segmentation module and an image fusion module, and is characterized in that it also includes a weakly supervised segmentation-based femoral neck fracture detection system. Methods for the detection of neck fractures,
[0125]The detection module inputs the acquired femoral neck X-rays into the constructed and trained detection neural network to detect the femoral part, and obtains the probability segmentation map Pprobability and the femoral neck region detection image P detec ;
[0126] Classification module, the femoral region is detected in the image P detec Input to the constructed and trained classification network to obtain the type of femoral fracture;
[0127] The weakly supervised segmentation module obtains the segmented fracture site and detects the ...
Embodiment 3
[0130] On the basis of Embodiment 1, the steps of constructing a neural network and segmenting a probability map in this embodiment include:
[0131] Step 1.1, input a set of femoral neck X-ray images P orig , set the initial convolution output channel 64;
[0132] Step 1.2, for the input image P orig Do two 3×3 convolutions, and the number of output channels per convolution is n 2 , batch normalization and ReLU operations are performed after each convolution, and a 2×2 maximum pooling operation is performed after the two convolutions are completed to extract the feature EIG_S2;
[0133] Step 1.3, take the feature EIG_S2 as the input feature, perform two 3×3 convolutions, and the number of output channels for each convolution is n 3 , n 3 =n 2 *2; when n 3 =512, the output feature is EIG_S3, and step 1.4 is executed, otherwise, the output feature EIG_S3 is used as the input feature of step 1.2, and step 1.2 is repeated;
[0134] Step 1.4, do two 3×3 convolutions on the ...
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