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Intelligent diagnosis value of preoperative T staging of colorectal cancer based on MR medical imaging

Colorectal cancer is a common malignant tumor in clinic. With the change of people's diet, living environment and living habits, the incidence of colorectal cancer has risen sharply in recent years, which poses a great threat to people's health and quality of life. This paper aims to inves...

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Autores principales: Wang, Junqing, Chen, Bingqian, Zhu, Jing, Zhang, Junfeng, Jiang, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979308/
https://www.ncbi.nlm.nih.gov/pubmed/36873937
http://dx.doi.org/10.3389/fgene.2023.1119990
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author Wang, Junqing
Chen, Bingqian
Zhu, Jing
Zhang, Junfeng
Jiang, Rui
author_facet Wang, Junqing
Chen, Bingqian
Zhu, Jing
Zhang, Junfeng
Jiang, Rui
author_sort Wang, Junqing
collection PubMed
description Colorectal cancer is a common malignant tumor in clinic. With the change of people's diet, living environment and living habits, the incidence of colorectal cancer has risen sharply in recent years, which poses a great threat to people's health and quality of life. This paper aims to investigate the pathogenesis of colorectal cancer and improve the efficiency of clinical diagnosis and treatment. This paper firstly introduces MR Medical imaging technology and related theories of colorectal cancer through literature survey, and then applies MR technology to preoperative T staging of colorectal cancer. 150 patients with colorectal cancer admitted to our hospital every month from January 2019 to January 2020 were used as research objects to carry out the application experiment of MR Medical imaging in the intelligent diagnosis of preoperative T staging of colorectal cancer, and to explore the diagnostic sensitivity, specificity and histopathological T staging diagnosis coincidence rate of MR Staging. The final study results showed that there was no statistical significance in the general data of stage T1-2, T3 and T4 patients (p > 0.05); for patients with preoperative T stage of colorectal cancer, the overall diagnosis coincidence rate of MR Was 89.73%, indicating that it was highly consistent with pathological T stage; compared with MR Staging, the overall diagnosis coincidence rate of CT for preoperative T staging of colorectal cancer patients was 86.73%, which was basically consistent with the diagnosis of pathological T staging. At the same time, three different dictionary learning depth techniques are proposed in this study to solve the shortcomings of long MR Scanning time and slow imaging speed. Through performance testing and comparison, it is found that the structural similarity of MR Image reconstructed by depth dictionary method based on convolutional neural network is up to 99.67%, higher than that of analytic dictionary and synthetic dictionary, which proves that it has the best optimization effect on MR Technology. The study indicated the importance of MR Medical imaging in preoperative T staging diagnosis of colorectal cancer and the necessity of its popularization.
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spelling pubmed-99793082023-03-03 Intelligent diagnosis value of preoperative T staging of colorectal cancer based on MR medical imaging Wang, Junqing Chen, Bingqian Zhu, Jing Zhang, Junfeng Jiang, Rui Front Genet Genetics Colorectal cancer is a common malignant tumor in clinic. With the change of people's diet, living environment and living habits, the incidence of colorectal cancer has risen sharply in recent years, which poses a great threat to people's health and quality of life. This paper aims to investigate the pathogenesis of colorectal cancer and improve the efficiency of clinical diagnosis and treatment. This paper firstly introduces MR Medical imaging technology and related theories of colorectal cancer through literature survey, and then applies MR technology to preoperative T staging of colorectal cancer. 150 patients with colorectal cancer admitted to our hospital every month from January 2019 to January 2020 were used as research objects to carry out the application experiment of MR Medical imaging in the intelligent diagnosis of preoperative T staging of colorectal cancer, and to explore the diagnostic sensitivity, specificity and histopathological T staging diagnosis coincidence rate of MR Staging. The final study results showed that there was no statistical significance in the general data of stage T1-2, T3 and T4 patients (p > 0.05); for patients with preoperative T stage of colorectal cancer, the overall diagnosis coincidence rate of MR Was 89.73%, indicating that it was highly consistent with pathological T stage; compared with MR Staging, the overall diagnosis coincidence rate of CT for preoperative T staging of colorectal cancer patients was 86.73%, which was basically consistent with the diagnosis of pathological T staging. At the same time, three different dictionary learning depth techniques are proposed in this study to solve the shortcomings of long MR Scanning time and slow imaging speed. Through performance testing and comparison, it is found that the structural similarity of MR Image reconstructed by depth dictionary method based on convolutional neural network is up to 99.67%, higher than that of analytic dictionary and synthetic dictionary, which proves that it has the best optimization effect on MR Technology. The study indicated the importance of MR Medical imaging in preoperative T staging diagnosis of colorectal cancer and the necessity of its popularization. Frontiers Media S.A. 2023-02-16 /pmc/articles/PMC9979308/ /pubmed/36873937 http://dx.doi.org/10.3389/fgene.2023.1119990 Text en Copyright © 2023 Wang, Chen, Zhu, Zhang and Jiang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Wang, Junqing
Chen, Bingqian
Zhu, Jing
Zhang, Junfeng
Jiang, Rui
Intelligent diagnosis value of preoperative T staging of colorectal cancer based on MR medical imaging
title Intelligent diagnosis value of preoperative T staging of colorectal cancer based on MR medical imaging
title_full Intelligent diagnosis value of preoperative T staging of colorectal cancer based on MR medical imaging
title_fullStr Intelligent diagnosis value of preoperative T staging of colorectal cancer based on MR medical imaging
title_full_unstemmed Intelligent diagnosis value of preoperative T staging of colorectal cancer based on MR medical imaging
title_short Intelligent diagnosis value of preoperative T staging of colorectal cancer based on MR medical imaging
title_sort intelligent diagnosis value of preoperative t staging of colorectal cancer based on mr medical imaging
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979308/
https://www.ncbi.nlm.nih.gov/pubmed/36873937
http://dx.doi.org/10.3389/fgene.2023.1119990
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