A Stacked Projection Reconstruction Method for Small-area Tumor Blocks after Segmentation

A small area, tumor technology, applied in the field of graphics and computer vision, can solve the problem of inapplicability, and achieve the effect of overcoming the volume effect

Active Publication Date: 2021-09-28
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

[0004] Aiming at the deficiencies of the existing medical diagnosis technology, the present invention provides a stacking projection reconstruction method of small-area tumor blocks after segmentation. After reconstruction, the texture information can accurately locate partitions and volumes intuitively, and reversely avoids the problem of inapplicability of specific parts.

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  • A Stacked Projection Reconstruction Method for Small-area Tumor Blocks after Segmentation
  • A Stacked Projection Reconstruction Method for Small-area Tumor Blocks after Segmentation
  • A Stacked Projection Reconstruction Method for Small-area Tumor Blocks after Segmentation

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Embodiment Construction

[0030] Aiming at medical imaging of different modalities of all organs such as brain, lung, heart, etc., the present invention provides a method for stacking projection reconstruction of a segmented small-area tumor block, which includes the following steps:

[0031] Step 1. Reduce the dimensionality of medical imaging data into discrete two-dimensional slice sequences, and use the improved fully convolutional neural network to perform large-scale segmentation of small-area tumor blocks on different modality slices;

[0032] Among them, reducing the dimensionality of medical image data into discrete two-dimensional slice groups includes the following steps:

[0033] Step 1-1, in order to avoid tumor site specificity, combine the built-in Slice() and Crop() to slice the pixel map of each case orthogonally from the center of gravity to form m sequence of slices, m The value is determined by the quality of clinical medical images to ensure the validity and reliability of reconst...

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Abstract

The present invention proposes a method for stacking projection reconstruction of small-area tumor blocks after segmentation. Among them, the method includes: step 1, reducing the dimensionality of medical image data into discrete two-dimensional slice sequences, using an improved full convolutional neural network to perform large-scale segmentation of small-area tumor blocks on slices of different modalities; step 2, Tumor-containing sections according to the similarity index patch Calibration, precise positioning of the tumor mass; step 3, stacking small-area tumor mass images, repeatedly constraining multi-column parallel filtering to offset a very small angle, and projecting the calibrated small-area tumor mass to reconstruct the patient body. The goal of the method of the present invention is to achieve rapid segmentation, precise positioning and reverse reconstruction of the disease body, and to display multi-dimensional structural information, to display the distribution and relative position of tumor tissues alone or in combination, and to promote emerging medical solutions such as image-guided minimally invasive surgery. development of.

Description

technical field [0001] The invention belongs to the technical fields of graphics and computer vision, and in particular relates to a stacking projection reconstruction method of a segmented small-area tumor mass. Background technique [0002] Medical imaging technology refers to the analysis and processing of patient image data through advanced computer software and hardware, which has become an important part of medical information construction. Among them, imaging technologies such as computed tomography (CT), magnetic resonance imaging (magnetic resonance imaging, MR), and digital radiography (digital radiography, DR) have a great impact on the diagnosis and treatment of tumors. value. The medical visualization interface can allow doctors to instruct and introduce relevant image information to patients in detail, intuitively and accurately understand the size, location and morphological characteristics of the entire lesion area, thereby improving the objectivity of clini...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T11/00G06T7/10G06T7/70G06T5/00G06F3/0484G06N3/04
CPCG06T11/003G06T7/10G06T7/70G06T5/002G06F3/04845G06T2207/30096G06N3/045
Inventor 谈玲马雯杰夏景明
Owner NANJING UNIV OF INFORMATION SCI & TECH
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