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US 10,420,535 B1Granted
Assisted detection model of breast tumor, assisted detection system thereof, and method for assisted detecting breast tumor
AssigneeChina Medical University Hospital
InventorsTzung-Chi Huang, Ken Ying-Kai Liao, Jiaxin Yu, Yang Hsien Lin, Po-Hsin Hsieh
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Abstract
An assisted detection system of breast tumor includes an image capturing unit and a non-transitory machine readable medium. The non-transitory machine readable medium storing a program which, when executed by at least one processing unit, determines a breast tumor type of the subject and predicts a probability of a tumor location of the subject. The program includes a reference database obtaining module, a first image preprocessing module, an autoencoder module, a classifying module, a second image preprocessing module and a comparing module.
Claims17
An assisted detection model of breast tumor, comprising following establishing steps:
- obtaining a reference database, wherein the reference database comprises a plurality of reference breast ultrasound images;
- performing an image preprocessing step, wherein the image preprocessing step is for dividing an image matrix value of each of the reference breast ultrasound images by a first normalization factor to obtain a reference value interval, and the reference value interval is between 0 and 1;
- performing a feature selecting step, wherein the feature selecting step is for selecting a feature matrix according to the reference database by using an autoencoder module, and the autoencoder module comprises:
- an encoder for compressing the reference value interval to obtain the feature matrix, wherein the encoder comprises a plurality of convolution layers and a plurality of pooling layers;
- and
- a decoder for reducing the feature matrix and comparing the reduced feature matrix with the reference breast ultrasound images to confirm that the feature matrix comprises key information in each of the reference breast ultrasound images, wherein the decoder comprises a plurality of convolution layers and a plurality of upsampling layers;
- and
- performing a classifying step, wherein the classifying step is for achieving a convergence of the feature matrix by using a deep learning classifier to obtain the assisted detection model of breast tumor;
- wherein the assisted detection model of breast tumor is used to determine a breast tumor type of a subject and predict a probability of a tumor location of the subject.
6 more elements
An assisted detection system of breast tumor, comprising:
- an image capturing unit for obtaining a target breast ultrasound image of a subject;
- and
- a non-transitory machine readable medium storing a program, which when executed by at least one processing unit, determines a breast tumor type of the subject and predicts a probability of a tumor location of the subject, the program comprising:
- a reference database obtaining module for obtaining a reference database, wherein the reference database comprises a plurality of reference breast ultrasound images;
- a first image preprocessing module for normalizing an image matrix value of each of the reference breast ultrasound images to obtain a reference value interval, wherein the reference value interval is between 0 and 1;
- an autoencoder module for selecting a feature matrix according to the reference database, the autoencoder module comprising:
- an encoder for compressing the reference value interval to obtain the feature matrix, wherein the encoder comprises a plurality of convolution layers and a plurality of pooling layers;
- and
- a decoder for reducing the feature matrix and comparing the reduced feature matrix with the reference breast ultrasound images to confirm that the feature matrix comprises key information in each of the reference breast ultrasound images, wherein the decoder comprises a plurality of convolution layers and a plurality of upsampling layers;
- a classifying module for achieving a convergence of the feature matrix by using a deep learning classifier to obtain an assisted detection model of breast tumor;
- a second image preprocessing module for normalizing an image matrix value of each of the target breast ultrasound image to obtain a target value interval, wherein the target value interval is between 0 and 1;
- and
- a comparing module for analyzing the target value interval by the assisted detection model of breast tumor to determine the breast tumor type of the subject and predict the probability of the tumor location of the subject.
10 more elements
Dependencies are inferred from the claim text.