Microscopic image color convolution removal method and cutting method based on non-negative matrix factorization (NMF)

A non-negative matrix decomposition, microscopic image technology, applied in image analysis, image enhancement, image data processing and other directions, can solve problems such as low accuracy and poor real-time performance, and achieve high accuracy, accurate shape, and eliminate human factors. effect of influence

Active Publication Date: 2014-12-10
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

[0006] The technical problem to be solved by the present invention is to overcome the shortcomings of poor real-time performance and low accuracy caused by color deconvolution of microscopic images in the prior art through human intervention, and to provide a microscopic image based on non-neg

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  • Microscopic image color convolution removal method and cutting method based on non-negative matrix factorization (NMF)
  • Microscopic image color convolution removal method and cutting method based on non-negative matrix factorization (NMF)
  • Microscopic image color convolution removal method and cutting method based on non-negative matrix factorization (NMF)

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[0022] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0023] The idea of ​​the present invention is to use the non-negative matrix decomposition method to separate the observation channels corresponding to different staining agents for the stained and marked tissue microscopic images, and to perform image segmentation based on the separated observation channels, which can not only realize fast and comprehensive Automated image processing and more accurate image segmentation results provide a more accurate basis for subsequent cell detection and pathological diagnosis and analysis.

[0024] The technical scheme of the present invention will be described in detail below by taking cell image segmentation as an example, wherein the tissue section sample is stained with hematoxylin-eosin (H-E), and the whole image segmentation process is as follows:

[0025] Step 1. Construct a new two-dimensional image matrix:...

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Abstract

The invention discloses a microscopic image color convolution removal method based on non-negative matrix factorization (NMF), and belongs to the image information processing technology filed. The microscopic image color convolution removal method based on the NMF is directed at a tissue microscopic image after dye marking, and uses an NMF method to separate observation channels corresponding to different coloring agents. The invention further discloses a microscopic image cutting method based on the NMF. The microscopic image cutting method based on the NMF is used to cut the image based on the observation channels separated through the NMF method, not only can achieve rapid and completely automatic image processing, but also obtain an accurate image cutting result, and provides accurate basis for subsequent cell detection and pathological diagnostic analysis. Compared with the prior art, the microscopic image color convolution removal method and the microscopic image cutting method based on the NMF can effectively improve microscopic image cutting accuracy, save computation time, and obtain the microscopic image good in visual effect.

Description

technical field [0001] The present invention relates to the technical field of image information processing, in particular to a microscopic image color deconvolution method and segmentation method based on Nonnegative Matrix Factorization (NMF for short). Background technique [0002] Pathology is the microscopic study of the morphological properties of cells. It plays a subjective and important role in the decision-making of treatment options. Especially in the diagnosis of some diseases including cancer, the analysis results of pathological images are still considered as the 'gold standard'. Pathology researchers have recognized the importance of quantitative analysis of pathological images. It can be used to support a clinician's diagnostic decision about a disease, and it can also help evaluate the treatment effect of a patient's disease. Quantitative analysis is not only crucial in the clinical field, but also in the field of applied research (such as drug developmen...

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Application Information

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IPC IPC(8): G06T5/00G06T7/00
Inventor 徐军项磊蒲雯静
Owner NANJING UNIV OF INFORMATION SCI & TECH
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