Support Vector Machine-Based Backprojection Algorithm for Detection of Gastric Cancer Lesions with Abdominal Endoscope Using Magnetic Resonance Imaging Images

Huajia Dai,Junfeng Yang,Yuhao Bian,Libin Wang,Gustavo Ramirez

doi:10.1155/2021/9964203

Huajia Dai, Junfeng Yang + Show 3 more

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https://doi.org/10.1155/2021/9964203

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Journal: Scientific programming	Publication Date: May 8, 2021
Citations: 3	License type: CC BY 4.0

Affiliation: Huadong Hospital

Abstract

This study was to analyze the diagnostic value of magnetic resonance imaging (MRI) for gastric cancer (GC) lesions and the treatment effect of complete laparoscopic radical resection (CLSRR). A malignant tumor recognition algorithm was constructed in this study based on the backprojection (BP) and support vector machine (SVM), which was named BPS. 78 GC patients were divided into an experimental group (received CLSRR) and a control group (received assisted laparoscopic radical resection (ALSRR)), with 39 cases in each group. It was found that the BPS algorithm showed lower relative mean square error (MSE) in axle x (OMSE, x) and axle y (OMSE, x), but the classification accuracy (CA) was the opposite ( P < 0.05 ). The postoperative hospital stay, analgesia duration, first exhaust time (FET), and first off-bed activity time (FOBA) for patients in the experimental group were less ( P < 0.05 ). The operation time of the experimental group (270.56 ± 90.55 min) was significantly longer than that of the control group (228.07 ± 75.26 min) ( P < 0.05 ). There were 3 cases of anastomotic fistula, 1 case of acute peritonitis, and 2 cases of lung infections in the experimental group, which were greatly less than those in the control group (7 cases, 4 cases, and 3 cases) ( P < 0.05 ). In short, the BPS algorithm was superior in processing MRI images and could improve the diagnostic effect of MRI images. The CLSRR could reduce the length of hospital stay and the probability of complications in GC patients, so it could be used as a surgical plan for the clinical treatment of advanced GC.

Highlights

Gastric cancer (GC) is a malignant tumor originating from the epithelium of the gastric mucosa
GC radical resection refers to the complete resection of the cancerous tissues of the stomach and the surrounding tissues that may be involved in the infiltration
It was found that the BPS algorithm showed visible smaller OMSE, x and OMSE, y as well as higher classification accuracy (CA) than the BP and support vector machine (SVM) algorithms (P < 0.05), which was similar to the results of Hu et al [17]. It indicated that the BPS algorithm constructed in magnetic resonance imaging (MRI) could show excellent performance in image processing and could improve the diagnostic effect of MRI images. e BPS algorithm was applied to 78 cases of GC patients for MRI diagnosis, and the results found that the diagnostic accuracies of MRI for GC T1, T2, T3, and T4 stage were 80.55%, 76.15%, 96.44%, and 62.45%, respectively

Summary

Introduction

Gastric cancer (GC) is a malignant tumor originating from the epithelium of the gastric mucosa. Half of early GC patients have no obvious clinical symptoms; only some of them have mild indigestion and other symptoms, such as upper abdominal pain, discomfort, slight fullness, pain, nausea, and belching. These symptoms are not unique to GC [3, 4]. GC radical resection refers to the complete resection of the cancerous tissues of the stomach and the surrounding tissues that may be involved in the infiltration It is mainly divided into three types: total gastrectomy, partial gastrectomy of the upper root, and partial gastrectomy of the lower root [6]

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