Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods

被引：0
|
作者：
Xinhui Wang
Qi Wan
Houjin Chen
Yanfeng Li
Xinchun Li
机构：
[1] Beijing Jiaotong University,School of Electronic and Information Engineering
[2] The First Affiliated Hospital of Guangzhou Medical University,Department of Radiology
来源：
European Radiology | 2020年 / 30卷
关键词：
Magnetic resonance imaging; Lung cancer; Radiomics; Machine learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：4595 / 4605
页数：10
相关论文
共 50 条
  • [21] Preoperative Prediction of Microsatellite Instability in Rectal Cancer Using Five Machine Learning Algorithms Based on Multiparametric MRI Radiomics
    Zhang, Yang
    Liu, Jing
    Wu, Cuiyun
    Peng, Jiaxuan
    Wei, Yuguo
    Cui, Sijia
    DIAGNOSTICS, 2023, 13 (02)
  • [22] Machine-learning approach to predict molecular subgroups of medulloblastoma using multiparametric MRI-based tumor radiomics
    Saju, Ann Christy
    Chatterjee, Abhishek
    Sahu, Arpita
    Gupta, Tejpal
    Krishnatry, Rahul
    Mokal, Smruti
    Sahay, Ayushi
    Epari, Sridhar
    Prasad, Maya
    Chinnaswamy, Girish
    Agarwal, Jai Prakash
    Goda, Jayant S.
    BRITISH JOURNAL OF RADIOLOGY, 2022, 95 (1134):
  • [23] Comparison of MRI Sequences to Predict ATRX Status Using Radiomics-Based Machine Learning
    Mora, Nabila Gala Nacul
    Akkurt, Burak Han
    Kasap, Dilek
    Bloemer, David
    Heindel, Walter
    Mannil, Manoj
    Musigmann, Manfred
    DIAGNOSTICS, 2023, 13 (13)
  • [24] Handcrafted MRI radiomics and machine learning: Classification of indeterminate solid adrenal lesions
    Stanzione, Arnaldo
    Cuocolo, Renato
    Verde, Francesco
    Galatola, Roberta
    Romeo, Valeria
    Mainenti, Pier Paolo
    Aprea, Giovanni
    Guadagno, Elia
    De Caro, Marialaura Del Basso
    Maurea, Simone
    MAGNETIC RESONANCE IMAGING, 2021, 79 : 52 - 58
  • [25] ComBat Harmonization for MRI Radiomics Impact on Nonbinary Tissue Classification by Machine Learning
    Leithner, Doris
    Nevin, Rachel B.
    Gibbs, Peter
    Weber, Michael
    Otazo, Ricardo
    Vargas, H. Alberto
    Mayerhoefer, Marius E.
    INVESTIGATIVE RADIOLOGY, 2023, 58 (09) : 697 - 701
  • [26] Multiparametric MRI From Simultaneous Rapid Acquisition Methods and Analysis Techniques Using Scoring, Machine Learning, Radiomics, and Deep Learning to the Generation of Novel Metrics
    Hagiwara, Akifumi
    Fujita, Shohei
    Kurokawa, Ryo
    Andica, Christina
    Kamagata, Koji
    Aoki, Shigeki
    INVESTIGATIVE RADIOLOGY, 2023, 58 (08) : 548 - 560
  • [27] Machine learning–based radiomics for histological classification of parotid tumors using morphological MRI: a comparative study
    Zhiying He
    Yitao Mao
    Shanhong Lu
    Lei Tan
    Juxiong Xiao
    Pingqing Tan
    Hailin Zhang
    Guo Li
    Helei Yan
    Jiaqi Tan
    Donghai Huang
    Yuanzheng Qiu
    Xin Zhang
    Xingwei Wang
    Yong Liu
    European Radiology, 2022, 32 : 8099 - 8110
  • [28] Predictive Study of Machine Learning-Based Multiparametric MRI Radiomics Nomogram for Perineural Invasion in Rectal Cancer: A Pilot Study
    Wang, Yueyan
    Chen, Aiqi
    Wang, Kai
    Zhao, Yihui
    Du, Xiaomeng
    Chen, Yan
    Lv, Lei
    Huang, Yimin
    Ma, Yichuan
    JOURNAL OF IMAGING INFORMATICS IN MEDICINE, 2025, 38 (02): : 1224 - 1235
  • [29] Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients
    Jia Wang
    Jingjing Chen
    Ruizhi Zhou
    Yuanxiang Gao
    Jie Li
    BMC Cancer, 22
  • [30] Effective Strategies for Deep Learning with Scarce Data for Prostate Lesion Classification Using Multiparametric MRI
    Karimi, D.
    Ruan, D.
    MEDICAL PHYSICS, 2017, 44 (06) : 3014 - 3014
12345