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深度学习技术调控甲状腺癌患者生活质量及免疫功能的研究。

Regulation of Quality of Life and Immune Function in Patients with Thyroid Cancer Treated by Deep Learning Technology.

机构信息

Department of General Surgery, the First Affiliated Hospital of Jiamusi University, Jiamusi 154000, Heilongjiang, China.

School of Clinical Medicine, Jiamusi University, Jiamusi 154000, Heilongjiang, China.

出版信息

Contrast Media Mol Imaging. 2022 Aug 30;2022:3281039. doi: 10.1155/2022/3281039. eCollection 2022.

Abstract

BACKGROUND

In order to explore the regulation of quality of life and immune function in patients with thyroid cancer after radiotherapy, a method based on deep learning technology was proposed. A deep learning detection method for thyroid cancer is proposed.

METHODS

It mainly includes three main modules: data preprocessing, thyroid cancer regional detection module, and thyroid cancer benign and malignant classification module. The data set in the experiment comes from LIDC-IDRI and is processed by the data preprocessing module to generate a standard data format that can be processed by the framework. The treatment of thyroid cancer can help patients relapse malignant thyroid cancer and prevent recurrence in advance.

RESULTS

The results showed that most patients are diagnosed because of obvious swelling of local thyroid mass and conscious compression symptoms in the neck. At this time, they often miss the best treatment time, so as to reduce the surgical effect.

CONCLUSIONS

The metastasis and invasion of cancer cells are fast, the cancerous lesions are easy to form adhesion with the surrounding tracheal tissue, and the cancer cells invade the surrounding soft tissue, which is also easy to cause the cancerous tissue not to be completely removed. . Therefore, deep learning technology is used to treat residual cancerous lesions to ensure the surgical effect.

摘要

背景

为了探讨甲状腺癌患者放疗后生活质量和免疫功能的调节,提出了一种基于深度学习技术的方法。提出了一种甲状腺癌的深度学习检测方法。

方法

主要包括三个主要模块:数据预处理、甲状腺癌区域检测模块和甲状腺癌良性和恶性分类模块。实验中的数据集来自 LIDC-IDRI,并通过数据预处理模块进行处理,生成可以由框架处理的标准数据格式。对甲状腺癌的治疗有助于患者复发恶性甲状腺癌,并提前预防复发。

结果

结果表明,大多数患者是由于局部甲状腺肿块明显肿胀和颈部自觉压迫症状而被诊断出来的。此时,他们往往错过了最佳的治疗时间,从而降低了手术效果。

结论

癌细胞的转移和侵袭速度快,癌性病变易与周围气管组织粘连,癌细胞侵犯周围软组织,也容易导致癌组织不能完全切除。因此,采用深度学习技术治疗残留癌灶,保证手术效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/82c0/9448623/4960214f831b/CMMI2022-3281039.001.jpg

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