Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

Journal: BioMed research international

Published Date: Oct 11, 2022

Abstract

PURPOSE: We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by image segmentation to build the model. The model is expected to help clinicians and provide additional information about what to do with first-visit patients.

Authors

Huanchun Yao

Department of Cancer, Shengjing Hospital of China Medical University, No. 36, Sanhao Street, Heping District, Shenyang, 110004 Liaoning Province, China.
Xinglong Zhang

Department of Hematology, The Fourth Affiliated Hospital of China Medical University, Shenyang, 110032 Liaoning Province, China.

Keywords

Carcinoma, Ovarian Epithelial Female Humans Lymph Nodes Lymphatic Metastasis Neural Networks, Computer Ovarian Neoplasms Positron Emission Tomography Computed Tomography Positron-Emission Tomography Retrospective Studies

External Resources

View on PubMed Access via DOI PubMed (36267845)

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

Abstract

Authors

Keywords

External Resources

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