Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy

被引:0
|
作者
Yangyang Zhu
Zheling Meng
Xiao Fan
Yin Duan
Yingying Jia
Tiantian Dong
Yanfang Wang
Juan Song
Jie Tian
Kun Wang
Fang Nie
机构
[1] Lanzhou University Second Hospital,Ultrasound Medical Center
[2] Lanzhou University,School of Artificial Intelligence
[3] CAS Key Laboratory of Molecular Imaging,Department of Ultrasound
[4] The State Key Laboratory of Management and Control for Complex Systems,Department of Ultrasound
[5] Institute of Automation,Beijing Advanced Innovation Center for Big Data
[6] Chinese Academy of Sciences,Based Precision Medicine, School of Medicine and Engineering
[7] University of Chinese Academy of Sciences,undefined
[8] Gansu Provincial Cancer Hospital,undefined
[9] People’s Hospital of Ningxia Hui Autonomous Region,undefined
[10] Beihang University,undefined
[11] Gansu Province Clinical Research Center for Ultrasonography,undefined
[12] Gansu Province Medical Engineering Research Center for Intelligence Ultrasound,undefined
来源
BMC Medicine | / 20卷
关键词
Deep learning; Cervical lymphadenopathy; Ultrasound; Reactive hyperplasia; Tuberculous lymphadenitis; Lymphoma; Metastatic carcinoma;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [41] Computer-aided diagnosis system for breast ultrasound images using deep learning
    Tanaka, Hiroki
    Chiu, Shih-Wei
    Watanabe, Takanori
    Kaoku, Setsuko
    Yamaguchi, Takuhiro
    PHYSICS IN MEDICINE AND BIOLOGY, 2019, 64 (23):
  • [42] DIAGNOSIS AND PROGNOSIS PREDICTION BY AUTOMATED MINING OF ULTRASOUND IMAGES WITH DEEP LEARNING IN OVARIAN CANCER
    Gao, Y.
    Zeng, S.
    Xu, X.
    Li, X.
    Mao, X.
    Qin, Y.
    Zhang, X.
    Shi, Y.
    Zhou, L.
    Li, L.
    Xing, H.
    Song, K.
    Yi, C.
    Tang, J.
    Lv, W.
    Kong, B.
    Xie, X.
    Ma, D.
    Li, X.
    Gao, Q.
    INTERNATIONAL JOURNAL OF GYNECOLOGICAL CANCER, 2018, 28 : 64 - 67
  • [43] Photoacoustic/fluorescence dual-modality cyanine-based probe for real-time imaging of endogenous cysteine and in situ diagnosis of cervical cancer in vivo
    Zou, Xiang
    Zhao, Yuping
    Lin, Weiying
    ANALYTICA CHIMICA ACTA, 2023, 1239
  • [44] Dual-Intended Deep Learning Model for Breast Cancer Diagnosis in Ultrasound Imaging
    Vigil, Nicolle
    Barry, Madeline
    Amini, Arya
    Akhloufi, Moulay
    Maldague, Xavier P. V.
    Ma, Lan
    Ren, Lei
    Yousefi, Bardia
    CANCERS, 2022, 14 (11)
  • [45] Ultrasound images-based deep learning radiomics nomogram for preoperative prediction of RET rearrangement in papillary thyroid carcinoma
    Yu, Jialong
    Zhang, Yihan
    Zheng, Jian
    Jia, Meng
    Lu, Xiubo
    FRONTIERS IN ENDOCRINOLOGY, 2022, 13
  • [46] Deep learning radiomics on grayscale ultrasound images assists in diagnosing benign and malignant of BI-RADS 4 lesions
    Yang, Liu
    Zhang, Naiwen
    Jia, Junying
    Ma, Zhe
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [47] Computer aided diagnosis system for cervical lymph nodes in CT images using deep learning
    Tekchandani, Hitesh
    Verma, Shrish
    Londhe, Narendra D.
    Jain, Rajiv Ratan
    Tiwari, Avani
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2022, 71
  • [48] Diagnosis of cervical lymph node metastasis with thyroid carcinoma by deep learning application to CT images
    Wang, Tiantian
    Yan, Ding
    Liu, Zhaodi
    Xiao, Lianxiang
    Liang, Changhu
    Xin, Haotian
    Feng, Mengmeng
    Zhao, Zijian
    Wang, Yong
    FRONTIERS IN ONCOLOGY, 2023, 13
  • [49] A novel intelligent thyroid nodule diagnosis system over ultrasound images based on deep learning
    Yi, Zhike
    Hao, Aimin
    Song, Wenfeng
    Li, Hongyi
    Li, Bowen
    2017 INTERNATIONAL CONFERENCE ON VIRTUAL REALITY AND VISUALIZATION (ICVRV 2017), 2017, : 150 - 155
  • [50] Rapid Segmentation and Diagnosis of Breast Tumor Ultrasound Images at the Sonographer Level Using Deep Learning
    Yang, Lei
    Zhang, Baichuan
    Ren, Fei
    Gu, Jianwen
    Gao, Jiao
    Wu, Jihua
    Li, Dan
    Jia, Huaping
    Li, Guangling
    Zong, Jing
    Zhang, Jing
    Yang, Xiaoman
    Zhang, Xueyuan
    Du, Baolin
    Wang, Xiaowen
    Li, Na
    BIOENGINEERING-BASEL, 2023, 10 (10):