Breast cancer lesion image segmentation method based on an end-to-end neural network

• Main Authors: GAO ZHAN, SHENG MEIHONG, TANG WEIXIA, SHAO YEQIN, TANG JIAHUAN
• Format: Patent
• Language: Chinese; English
• Published: 10.11.2020
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS

The invention discloses a breast cancer lesion image segmentation method based on an end-to-end neural network. The breast cancer lesion image segmentation method comprises the following steps: step 1, labeling by hands: marking a lesion area on data according to experience of a doctor; step 2, preprocessing data: preprocessing the three-dimensional image data, and cutting the three-dimensional image data into an image size suitable for a neural network; step 3, selecting a model: selecting an improved end-to-end neural network model; step 4, training a model: training an optimal model on themarked training set by using an improved network model; step 5, predicting data: predicting a focus area by using the trained model; and step 6, evaluating a result: measuring the accuracy of focus segmentation by utilizing corresponding evaluation indexes. According to the improved end-to-end neural network provided by the invention, a hole residual network is used on an original resolution image, and rich feature inform