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Detection of Lymph Nodes in T2 MRI Using Neural Network Ensembles

文献类型： 会议论文

第一作者： Zhiyong Lu

作者： Zhiyong Lu 1 ; Ronald M. Summers 2 ; Tejas Sudharshan Mathai 2 ; Sungwon Lee 2 ; Daniel C. Elton 2 ; Thomas C. Shen 2 ; Yifan Peng 1 ;

作者机构： 1.National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health

2.Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health

关键词： MRI;T2;Lymph node;Detection;Deep learning

会议名称： International Workshop on Machine Learning in Medical Imaging

主办单位：

页码： 682-691

摘要： Reliable localization of abnormal lymph nodes in T2 Magnetic Resonance Imaging (MRI) scans is needed for staging and treatment of lymphoproliferative diseases. Radiologists need to accurately characterize the size and shape of the lymph nodes and may require an additional contrast sequence such as diffusion weighted imaging (DWI) for staging confirmation. The varied appearance of lymph nodes in T2 MRI makes staging for metastasis challenging. Moreover, radiologists often times miss smaller lymph nodes that could be malignant over the course of a busy clinical day. To address these imaging and workflow issues, in this pilot work we aim to localize potentially suspicious lymph nodes for staging. We use state-of-the-art detection neural networks to localize lymph nodes in T2 MRI scans acquired through a variety of scanners and exam protocols, and employ bounding box fusion techniques to reduce false positives (FP) and boost detection accuracy. We construct an ensemble of the best detection models to identify potential lymph node candidates for staging, obtaining a 71.75% precision and 91.96% sensitivity at 4 FP per image. To the best of our knowledge, our results improve upon the current state-of-the-art techniques for lymph node detection in T2 MRI scans.

分类号： tp391.41-53

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