基于深度学习方法的MRI骨癌检测与分期图像分类

E. Lingappa, L. Parvathy
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引用次数: 0

摘要

致癌基因的突变可以从父母遗传给后代。或者是因为DNA因暴露在无保护的环境中而老化。癌症是由不受控制的细胞发育引起的,可能是致命的。骨癌开始时,正常功能的骨细胞经历恶性转化和增殖失控,导致肿瘤。说到骨癌,发病率和严重程度都很高。为了有效地治疗骨癌,早期诊断和分期是必不可少的。本研究利用CT和MRI结合卷积神经网络检测骨恶性肿瘤。该技术的准确性通过100例已被验证的患者的骨核磁共振成像进行了评估。在这个分析中,cnn被用来确定骨肿瘤是良性的还是恶性的。使用该方法对骨癌进行分类的准确率很高(93.75%)。
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Image Classification with Deep Learning Methods for Detecting and Staging Bone Cancer from MRI
Mutations in cancer-causing genes can be passed down from parents to offspring. or because of DNA dam age from unprotected exposures to the elements. Cancer, which is brought on by unchecked cell development, can be lethal. Bone cancer begins when normally functioning bone cells undergo a malignant transformation and proliferate out of control, resulting in a tumour. When it comes to cancers of the bones, the incidence and severity rank high. To treat bone cancer effectively, early diagnosis and staging are essential. This study utilized CT and MRI with a Convolutional Neural Network to detect bone malignancy. The accuracy of the suggested technique was evaluated using 100 bone MRIs from patients who had already been validated. In this analysis, CNNs are utilised to determine if a bone tumour is benign or malignant. Classifying bone cancer using the proposed method is highly accurate (93.75 percent).
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