Label-free pathological image feature extraction method based on spatial position information

The invention discloses a label-free pathological image feature extraction method based on spatial position information, which does not need to manually label lesions, constructs a data set and labels by means of a self-supervised algorithm and by using information such as spatial positions and zoom...

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Hauptverfasser: ZHANG JINGYI, SHE PAN, ZHANG BOQIANG, WANG YU, LIU YICONG, LU CHANGQING
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creator ZHANG JINGYI
SHE PAN
ZHANG BOQIANG
WANG YU
LIU YICONG
LU CHANGQING
description The invention discloses a label-free pathological image feature extraction method based on spatial position information, which does not need to manually label lesions, constructs a data set and labels by means of a self-supervised algorithm and by using information such as spatial positions and zoom magnifications of different pathological image blocks, and is used for extracting pathological image features. And a correlation model is trained, so that extraction of pathological image features and subsequent tasks are completed. Compared with an existing deep learning algorithm based on supervision and weak supervision, the method is easier to implement, on one hand, similar difference data pairs are automatically constructed by utilizing a self-supervised learning mode and spatial position information, manual annotation is not needed, the data set obtaining difficulty is greatly reduced, and a large amount of cost is saved; and on the other hand, a novel training framework is constructed, the similarity diffe
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
title Label-free pathological image feature extraction method based on spatial position information
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