Pancreatic tumor image segmentation method based on dense connection network transfer learning

A dense connection and pancreatic tumor technology, applied in the field of image processing, can solve the problems of low segmentation accuracy of pancreatic tumors, the small number of marked images without attention, and the inability to meet the needs of automatic delineation of pancreatic tumor areas, so as to improve performance and learn easily Effect

Pending Publication Date: 2021-11-26
XIDIAN UNIV
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Problems solved by technology

[0007] The above-mentioned existing pancreatic tumor segmentation methods do not pay attention to the problem of the small number of labeled images available in medical image segmentation, and only use images of one modality, that is, pancreatic tumor C

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  • Pancreatic tumor image segmentation method based on dense connection network transfer learning
  • Pancreatic tumor image segmentation method based on dense connection network transfer learning
  • Pancreatic tumor image segmentation method based on dense connection network transfer learning

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Embodiment Construction

[0032] The implementation and effects of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0033] refer to figure 1 , the implementation steps of the present invention include as follows:

[0034] Step 1. Construct positron emission tomography PET and nuclear magnetic resonance imaging MRI data sets, and divide training set and test set.

[0035] (1.1) Obtain positron emission tomography PET data and nuclear magnetic resonance imaging MRI data from the hospital;

[0036] (1.2) Based on the position of the nuclear magnetic resonance MRI image, use 3D slicer software to adjust the spatial position of the PET image of the same patient's positron emission tomography tomography, so that it overlaps with the nuclear magnetic resonance MRI image, and rotate randomly in turn , horizontal flip and vertical flip, respectively expand the amount of data to 8 times the original;

[0037] (1.3) Cut the size of the expanded PET ...

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Abstract

The invention discloses a pancreatic tumor image segmentation method based on dense connection network transfer learning, and the method comprises the steps: obtaining PET (positron emission computed tomography) and MRI (magnetic resonance imaging), carrying out the preprocessing of the PET and MRI, and dividing the PET and MRI into a training set and a test set; constructing a segmentation network, and training the segmentation network by using a PET training data set to obtain a network parameter W1 after one-time training; setting an initial parameter of a feature extraction module in the segmentation network as a value of a corresponding module in W1 by using a migration strategy, randomly initializing parameters of other modules, and retraining the segmentation network by using an MRI image training set to obtain a secondarily trained network parameter W2; and inputting the MRI test set into a segmentation network taking W2 as a network parameter to obtain a segmentation result. The method improves the performance of MRI image segmentation, solves the problem that a network is difficult to train for a small data set in the prior art, and can be used for assisting a doctor to complete automatic target region sketching before pancreatic tumor treatment.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for segmenting images of pancreatic tumors, which can be used to help doctors complete automatic target area delineation before pancreatic tumor treatment. Background technique [0002] At present, pancreatic tumor is still one of the deadliest malignant tumors in the world, and the incidence rate is increasing year by year. According to GLOBOCAN 2020, the latest global cancer burden report released by the International Cancer Institute in 2020, the estimated number of new cases of pancreatic tumors in the world in 2020 is nearly 495,700, and the number of deaths is about 466,000. Due to the poor prognosis of pancreatic tumors, the number of deaths caused by them is almost as high as the number of new cases, and it is the seventh leading cause of death from malignant tumors in both men and women. Pancreatic tumors are expected to overtake breast can...

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Application Information

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IPC IPC(8): G06T7/00G06T7/11G06T7/136G06T7/194G06K9/32G06K9/38G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06T7/11G06T7/136G06T7/194G06N3/084G06T2207/10088G06T2207/10104G06T2207/20081G06T2207/20084G06T2207/30096G06N3/047G06N3/048G06N3/045G06F18/241G06F18/2415
Inventor 缑水平续溢男童诺郭璋李睿敏陈姝喆刘波
Owner XIDIAN UNIV
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