蒙太奇方法利用卷积神经网络和脑MRI改进了疑似急性缺血性中风的分类。

IF 1.7 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Radiological Physics and Technology Pub Date : 2024-03-01 Epub Date: 2023-11-07 DOI:10.1007/s12194-023-00754-x
Daisuke Oura, Masayuki Gekka, Hiroyuki Sugimori
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引用次数: 0

摘要

本研究探讨了将四幅不同的磁共振图像合并为一幅图像的蒙太奇方法在深度学习方法自动诊断急性缺血性脑卒中(AIS)中的有用性。蒙太奇图像由扩散加权图像(DWI)、流体衰减反转恢复(FLAIR)、动脉旋转标记(ASL)和表观扩散系数(ASL。将蒙太奇方法与FLAIR、ASL和ADC组成的伪彩色图(pCM)进行了比较。473例AIS患者被分为四类:机械血栓切除术、保守治疗、出血和其他疾病。结果表明,蒙太奇图像在准确性方面显著优于pCM(蒙太奇图 = 0.76 ± 0.01,pCM = 0.54 ± 0.05)和曲线下面积(AUC)(蒙太奇图像 = 0.94 ± 0.01,pCM = 0.76 ± 0.01)。这项研究证明了蒙太奇方法的有用性及其克服pCM局限性的潜力。
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The montage method improves the classification of suspected acute ischemic stroke using the convolution neural network and brain MRI.

This study investigated the usefulness of the montage method that combines four different magnetic resonance images into one images for automatic acute ischemic stroke (AIS) diagnosis with deep learning method. The montage image was consisted from diffusion weighted image (DWI), fluid attenuated inversion recovery (FLAIR), arterial spin labeling (ASL), and apparent diffusion coefficient (ASL). The montage method was compared with pseudo color map (pCM) which was consisted from FLAIR, ASL and ADC. 473 AIS patients were classified into four categories: mechanical thrombectomy, conservative therapy, hemorrhage, and other diseases. The results showed that the montage image significantly outperformed pCM in terms of accuracy (montage image = 0.76 ± 0.01, pCM = 0.54 ± 0.05) and the area under the curve (AUC) (montage image = 0.94 ± 0.01, pCM = 0.76 ± 0.01). This study demonstrates the usefulness of the montage method and its potential for overcoming the limitations of pCM.

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来源期刊
Radiological Physics and Technology
Radiological Physics and Technology RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
3.00
自引率
12.50%
发文量
40
期刊介绍: The purpose of the journal Radiological Physics and Technology is to provide a forum for sharing new knowledge related to research and development in radiological science and technology, including medical physics and radiological technology in diagnostic radiology, nuclear medicine, and radiation therapy among many other radiological disciplines, as well as to contribute to progress and improvement in medical practice and patient health care.
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