In this work, we propose a deep learning algorithm for fast and accurate cysts detection in sequential 2-D images. Experiments on 507 RGB immunofluorescence ...
Experiments on 507 RGB immunoflu- orescence images of 8 kidney tubules show that the proposed U-Net-based deep-learning solution can automatically segment ...
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Apr 27, 2024 · This intelligent method can estimate and predict the types of brain cysts by the provided medical images. The experimental results demonstrate ...
Feb 3, 2024 · Method. Deep learning algorithms can provide powerful and effective solutions for automated segmentation of polycystic kidney tubules. ...
In this study, we developed, validated, and deployed a segmentation model using a U-Net architecture with an EfficientNet encoder for accurate polycystic kidney ...
Missing: tubules | Show results with:tubules
Apr 5, 2021 · Thus, in this paper, we propose a deep learning model for 3D instance cyst segmentation in order to measure total cyst volume (TCV) as well as ...
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We propose a set of fully convolutional networks for kidney and cyst segmentation in micro-CT images, based on the U-Net architecture, to compare them and ...
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Cyst segmentation on kidney tubules by means of U-Net deep-learning models · Abstract · Authors · BibTeX · References · Bibliographies · Reviews · Related ...
A Deep Learning Approach for Automated Segmentation of ...
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Conclusions: We developed a fully automated segmentation method to measure TKV that excludes exophytic cysts and has an accuracy similar to that of a human ...
segmentation of liver cysts using deep learning (DL) models. Materials and Methods: A self-configured UNet-based platform (nnU-Net) was trained with 40.