Kinetic heterogeneity features on breast DCE-MRI as prognostic markers of breast cancer recurrence

被引:0
|
作者
Mahrooghy, M.
Ashraf, A. B.
Gavenonis, S. C.
Daye, D.
Mies, C.
Feldman, M.
Rosen, M.
Kontos, D.
机构
[1] Univ Penn, Philadelphia, PA 19104 USA
[2] Christiana Care Hlth Syst, Newark, DE USA
关键词
D O I
10.1158/0008-5472.SABCS13-P2-02-04
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
P2-02-04
引用
收藏
页数:2
相关论文
共 50 条
  • [11] Assessing heterogeneity in DCE-MRI data of breast cancer to predict treatment response
    Syed, Anum
    Sorace, Anna G.
    Barnes, Stephanie L.
    Arlinghaus, Lori
    Li, Xia
    Yankeelov, Thomas E.
    CANCER RESEARCH, 2017, 77
  • [12] Association between Bilateral Asymmetry of Kinetic Features Computed from the DCE-MRI Images and Breast Cancer
    Yang, Qian
    Li, Lihua
    Zhang, Juan
    Zhang, Chengjie
    Zheng, Bin
    MEDICAL IMAGING 2013: COMPUTER-AIDED DIAGNOSIS, 2013, 8670
  • [13] Heterogeneity Wavelet Kinetics from DCE-MRI for Classifying Gene Expression Based Breast Cancer Recurrence Risk
    Mahrooghy, Majid
    Ashraf, Ahmed B.
    Daye, Dania
    Mies, Carolyn
    Feldman, Michael
    Rosen, Mark
    Kontos, Despina
    MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2013, PT II, 2013, 8150 : 295 - 302
  • [14] Exploring Kinetic Curves Features for the Classification of Benign and Malignant Breast Lesions in DCE-MRI
    Li, Zixian
    Zhong, Yuming
    Wang, Yi
    2024 IEEE 37TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, CBMS 2024, 2024, : 496 - 501
  • [15] Molecular subtypes classification of breast cancer in DCE-MRI using deep features
    Hasan, Ali M.
    Al-Waely, Noor K. N.
    Aljobouri, Hadeel K.
    Jalab, Hamid A.
    Ibrahim, Rabha W.
    Meziane, Farid
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 236
  • [16] Prediction of Histological Grade in Breast Cancer by Combining DCE-MRI and DWI Features
    Zhao, Wenrui
    Fan, Ming
    Xu, Maosheng
    Li, Lihua
    MEDICAL IMAGING 2019: IMAGING INFORMATICS FOR HEALTHCARE, RESEARCH, AND APPLICATIONS, 2019, 10954
  • [17] DCE-MRI radiomics features for predicting breast cancer neoadjuvant therapy response
    Kontopodis, E.
    Manikis, G. C.
    Skepasianos, I.
    Tzagkarakis, K.
    Nikiforaki, K.
    Papadakis, G. Z.
    Maris, T. G.
    Papadaki, E.
    Karantanas, A.
    Marias, K.
    2018 IEEE INTERNATIONAL CONFERENCE ON IMAGING SYSTEMS AND TECHNIQUES (IST), 2018, : 203 - 208
  • [18] Molecular subtypes classification of breast cancer in DCE-MRI using deep features
    Hasan, Ali M.
    Al-Waely, Noor K.N.
    Aljobouri, Hadeel K.
    Jalab, Hamid A.
    Ibrahim, Rabha W.
    Meziane, Farid
    Expert Systems with Applications, 2024, 236
  • [19] DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response
    Thibault, Guillaume
    Tudorica, Alina
    Afzal, Aneela
    Chui, Stephen Y-C
    Naik, Arpana
    Troxell, Megan L.
    Kemmer, Kathleen A.
    Oh, Karen Y.
    Roy, Nicole
    Jafarian, Neda
    Holtorf, Megan L.
    Huang, Wei
    Song, Xubo
    TOMOGRAPHY, 2017, 3 (01) : 23 - 32
  • [20] Correlation Analysis of Breast Cancer DWI Combined with DCE-MRI Imaging Features with Molecular Subtypes and Prognostic Factors
    Yuan, Congru
    Jin, Feng
    Guo, Xiuling
    Zhao, Sheng
    Li, Wei
    Guo, Haidong
    JOURNAL OF MEDICAL SYSTEMS, 2019, 43 (04)