Femoral marrow cavity type detection method and system

A technology of bone marrow cavity and femur, which is applied in the field of detection of femoral cavity type, can solve the problems of unautomated tools and methods, and achieve the effect of improving detection speed and ensuring accuracy

Pending Publication Date: 2021-11-02
瓴域影诺北京科技有限公司
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In terms of judging the type of femur, at present it is mainly the doctor's active measurement and delineation, and there are no automated tools and methods

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  • Femoral marrow cavity type detection method and system
  • Femoral marrow cavity type detection method and system
  • Femoral marrow cavity type detection method and system

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Embodiment Construction

[0069] The implementation mode of the present invention is illustrated by specific specific examples below, and those who are familiar with this technology can easily understand other advantages and effects of the present invention from the contents disclosed in this description. Obviously, the described embodiments are a part of the present invention. , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0070] With the development of convolutional neural network, it is possible to directly locate the femoral region, and then automatically calculate the scintillation index of the medullary cavity through image processing, and realize an efficient detection algorithm based on deep learning, which has high application value and clinical significance. Traditional algorithms need to adjust different ...

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Abstract

The embodiment of the invention discloses a femoral marrow cavity type detection method and system, and the method comprises the steps: carrying out the X-ray detection of a hip joint based on deep learning, and obtaining the left and right femoral detection images of the hip joint; performing noise reduction processing on the left and right femur images to obtain left and right femur edge images; positioning straight line positions of the left and right femur edge images through a Hough straight line method, and fitting a femur marrow cavity central axis; cutting out the lower half part of the femur, and locating the isthmus area of the femur and the area 2 cm above a lesser trochanter; calculating a medullary cavity flicker index according to the length of the upper 2cm femoral section line and the length of the narrowest region of the femoral medullary cavity so as to judge the type of the femur according to the medullary cavity flicker index. The method does not depend on the threshold excessively, is more robust, and improves the detection speed while guaranteeing the precision.

Description

technical field [0001] The embodiment of the present application relates to the field of artificial intelligence medical technology, and in particular to a method and system for detecting the type of femoral medullary cavity. Background technique [0002] Hip replacement is an important treatment for hip-related diseases. During the treatment process, the accurate matching of the prosthesis is related to the success of the operation. Therefore, finding a prosthesis that matches the femur is an important clinical goal, so the ability to accurately identify the type of femur in X-ray images is important for judging the type of prosthesis. Clinical value and practical significance. [0003] Noble et al proposed to use the scintillation index of the medullary cavity to guide the classification of the proximal femoral medullary cavity and the design and selection of the total hip replacement prosthesis. The judgment of femoral type affects the selection of prosthetic stem, so j...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/73G06T5/20G06T5/00G06N3/08G06K9/62A61B6/00
CPCG06T7/0012G06T5/002G06T7/73A61B6/505G06N3/08G06T7/11G06T5/20G06T2207/20081G06T2207/30008G06T2207/20032G06F18/241
Inventor 怀晓晨穆红章
Owner 瓴域影诺北京科技有限公司
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