Search alternatives:
segmentation algorithm » selection algorithm (Expand Search)
bayesian optimization » based optimization (Expand Search)
wave bayesian » naive bayesian (Expand Search), a bayesian (Expand Search), art bayesian (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary wave » binary image (Expand Search)
segmentation algorithm » selection algorithm (Expand Search)
bayesian optimization » based optimization (Expand Search)
wave bayesian » naive bayesian (Expand Search), a bayesian (Expand Search), art bayesian (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary wave » binary image (Expand Search)
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<b>Multimodal MRI radiomics</b><b> based on </b><b>habitat subregions of the tumor microenvironment</b><b> for predicting risk stratification in glioblastoma</b>
Published 2025“…</p><p dir="ltr">A fully automated approach involving label fusion from multiple deep learning algorithms was used to segment distinct tumor subregions histologically. …”
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Dense block structure.
Published 2024“…This paper proposes a network model based on the combination of U-net and DenseNet to solve the problems of class imbalance in multi-modal brain tumor image segmentation and the loss of effective information features caused by the integration of features in the traditional U-net network. …”
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Structure diagram of a transition layer.
Published 2024“…This paper proposes a network model based on the combination of U-net and DenseNet to solve the problems of class imbalance in multi-modal brain tumor image segmentation and the loss of effective information features caused by the integration of features in the traditional U-net network. …”
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Dense-U-net network structure.
Published 2024“…This paper proposes a network model based on the combination of U-net and DenseNet to solve the problems of class imbalance in multi-modal brain tumor image segmentation and the loss of effective information features caused by the integration of features in the traditional U-net network. …”
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Flowchart of software workflow.
Published 2021“…Images are then segmented using the chosen segmentation algorithm to generate a binary mask (d). …”
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Images of mouse popliteal lymph node vascular structure derived using phase-contrast synchrotron micro-computed tomography (µCT)
Published 2019“…The freeze-dried samples were scanned with high-resolution synchrotron tomography and the radiographs were reconstructed into stack images using a phase-retrieval algorithm. The images were pre-processed by removing the pipette tip image using a cone crop before intensity-based segmentation and manual artefact processing. …”
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Table_2_Radiomics analysis of contrast-enhanced CT scans can distinguish between clear cell and non-clear cell renal cell carcinoma in different imaging protocols.docx
Published 2022“…A support vector machine algorithm-based binary classifier (SVC) was constructed to predict tumor types and its performance was evaluated based-on receiver operating characteristic curve (ROC) analysis. …”