Semi-automatic tumor segmentation of rectal cancer based on functional magnetic resonance imaging

Franziska Knuth,Aurora R Groendahl,René M Winter,Turid Torheim,Anne Negård,Stein Harald Holmedal,Kine Mari Bakke,Sebastian Meltzer,Cecilia M Futsæther,Kathrine R Redalen

Physics and Imaging in Radiation Oncology（2022）

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摘要

•Machine learning on magnetic resonance images (MRI) was used for tumor segmentation.•Voxelwise machine learning with morphological post-processing achieved good segmentation results.•Combining T2-weighted with functional MRI improved semi-automatic tumor segmentation.•Dynamic contrast enhanced MRI was the most valuable functional MRI information.•Tumor volume and interobserver variation were linked to measured segmentation quality.

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关键词

ADA,DICE,DME,DW,IQR,LDA,MED,MRI,MSD,SVM,QDA

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