Choroid sublayer and choroid vessel segmentation network model and training method thereof

A network model and choroidal technology, applied in character and pattern recognition, image analysis, image data processing, etc., can solve the problem of poor segmentation accuracy of choroidal blood vessels

Pending Publication Date: 2022-04-26
PEKING UNIV FIRST HOSPITAL
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Problems solved by technology

[0004] In view of this, the embodiment of the present invention provides a choroidal sublayer and choroidal vessel segmentation net

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  • Choroid sublayer and choroid vessel segmentation network model and training method thereof
  • Choroid sublayer and choroid vessel segmentation network model and training method thereof
  • Choroid sublayer and choroid vessel segmentation network model and training method thereof

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[0025] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0026] The terms "first", "second", "third", "fourth" and the like in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily to describe specific sequence or sequence. It is to be understood that the terms so used are interchangeable under appropriate ...

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Abstract

The invention discloses a choroid sublayer and choroid vessel segmentation network model and a training method thereof, and the model comprises a sharing encoder module which is used for carrying out the down-sampling and feature extraction of a to-be-segmented image, and obtaining a first sharing feature; the shared decoder module is used for acquiring a first shared feature and performing up-sampling to obtain a second shared feature; the first decoder module is used for extracting choroid sublayer segmentation specific features in the second shared features; the second decoder module is used for extracting choroidal blood vessel segmentation specific features in the second shared features; and the classification module is used for calculating a segmentation result of the to-be-segmented image according to the second shared feature, the choroid sublayer segmentation specificity feature and the choroid blood vessel segmentation specificity feature. According to the invention, segmentation of choroid sublayers and choroid blood vessels is realized by arranging the five modules, namely, multi-task segmentation is realized through a multi-stream network structure.

Description

technical field [0001] The invention relates to the technical field of image segmentation, in particular to a choroidal sublayer and choroidal blood vessel segmentation network model and a training method thereof. Background technique [0002] Located between the retina and the sclera, the choroid is one of the most vascularized structures in the body, providing nutrients to the outer layers of the retina and playing a vital role in the human visual system. In clinical practice, optical coherence tomography (OCT) can separate the structures of the choroid from the retinal interior and is an effective method widely used in neurology, ophthalmology, gastroenterology and cardiology. To analyze ocular diseases based on OCT, researchers proposed quantitative choroidal biomarkers, such as choroidal thickness (CT), choroidal volume (CV), choroidal vascular density (CVD), choroidal Vascular index (choroidal vascularity index, CVI). Although these biomarkers can quantitatively refl...

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Application Information

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IPC IPC(8): G06T7/10G06K9/62G06V10/774G06V10/764
CPCG06T7/10G06T2207/30101G06F18/241G06F18/214
Inventor 杨柳李俊猛朱瑞琳顾枭鹏张雅娣荣蓓卢闫晔朱磊
Owner PEKING UNIV FIRST HOSPITAL
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