Novel computer aided diagnostic models on multimodality medical images to differentiate well differentiated liposarcomas from lipomas approached by deep learning methods.

Journal: Orphanet journal of rare diseases
Published Date:

Abstract

BACKGROUND: Deep learning methods have great potential to predict tumor characterization, such as histological diagnosis and genetic aberration. The objective of this study was to evaluate and validate the predictive performance of multimodality imaging-derived models using computer-aided diagnostic (CAD) methods for prediction of MDM2 gene amplification to identify well-differentiated liposarcoma (WDLPS) and lipoma.

Authors

  • Yuhan Yang
    West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China. Electronic address: yyh_1023@163.com.
  • Yin Zhou
    West China Hospital, Sichuan University, Guoxue Road 37, Chengdu, 610041, China. Electronic address: 653508203@qq.com.
  • Chen Zhou
    West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China. Electronic address: 13258389785@163.com.
  • Xuelei Ma