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Method for identification and localization of images using triplet loss and predicted regions and medium

A triplet, test image technique, applied in the field of image analysis

Pending Publication Date: 2021-09-14
FUJIFILM BUSINESS INNOVATION CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Although there are multiple medical datasets where the presence of diseases is annotated, there are few annotations of disease locations

Method used

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  • Method for identification and localization of images using triplet loss and predicted regions and medium
  • Method for identification and localization of images using triplet loss and predicted regions and medium
  • Method for identification and localization of images using triplet loss and predicted regions and medium

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Embodiment Construction

[0016] The following detailed description provides further details of the drawings and example implementations of the present application. For clarity, the numerals and descriptions of redundant elements between the drawings are omitted. Terms used throughout the specification are provided by way of example and are not intended to be limiting. For example, use of the term "automatic" may refer to a fully automatic or semi-automatic implementation, involving user or operator control of particular aspects of the implementation, depending on the desired implementation by one of ordinary skill in the art practicing the implementation of the present application Way. Furthermore, sequential terms such as "first," "second," "third," etc. may be used in the specification and claims for labeling purposes only and should not be limited to indicating that the described actions or items occur in the order described . Actions or items may be sequenced into a different order or may be pe...

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Abstract

The invention provides a method for identification and localization of images using triplet loss and predicted regions and a medium. A method and a system for classifying image features using a neural network and system is provided. The method includes training the neural network using triplet loss processes including receiving an anchor image, selecting a positive image and a negative image, generating a image embedding associated with each of the anchor image, the positive image, and the negative image, classifying image features extracted from the anchor image based on the image embedding of the anchor image, determining an image label location associated with the classified image features, extracting features associated with the determined image label location, and classifying the features associated with the determined image label location; and combining the multi-label loss with localized image classification loss and the triplet loss using a weighted loss sum.

Description

technical field [0001] The present disclosure relates to image analysis, and more particularly, to systems and methods for automatically identifying and locating image regions. Background technique [0002] In the application of the prior art, the identification and localization of diseases in medical images has been applied to the segmentation of diseases in medical images. In addition, it can be used to associate textual descriptions of diseases in medical reports with image regions discussed in the report. Prior art methods have allowed automatic segmentation of organs. By understanding which diseases are present in the image and the approximate location of each disease, organ segmentation methods can be applied to disease segmentation. This, in turn, will improve the efficiency of measuring disease size in medical images. [0003] Furthermore, in the prior art, the ability to perform disease localization also allows for linking or highlighting of the location in the m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/13G06K9/62G06N3/04G06N3/08G06V10/764G06V10/776
CPCG06T7/0012G06T7/11G06T7/13G06N3/08G06T2207/20081G06T2207/20084G06T2207/30061G06N3/045G06F18/241G06V2201/03G06V10/82G06V10/809G06V10/776G06V10/764G06F18/254G06T3/40G06N20/00G06T3/60G06F18/211G06F18/214
Inventor 张诚弗朗辛·陈陈殷盈
Owner FUJIFILM BUSINESS INNOVATION CORP
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