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Apr 5, 2023 · This article compares the performance of U-net and SegNet neural networks for nuclei segmentation in cervical images.
This article compares the performance of U-net and SegNet neural networks for nuclei segmentation in cervical images.
We present a new framework based on deep convolutional neural networks (DCNNs) to automatically segment overlapping cells in digital cytology. A double-window ...
Oct 3, 2023 · We have proposed a deep learning model, namely C-UNet (Cervical-UNet), to segment cervical nuclei from overlapped, fuzzy, and blurred cervical cell smear ...
Sep 19, 2024 · In this study, we systematically review the current developments in cervical cell image analysis with DL methods.
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This paper presents an approach to whole cervical cell segmentation using a mask regional convolutional neural network (Mask R-CNN) and classifies this ...
Nuclear segmentation in cervical cell images is a crucial technique for automatic cytopathology diagnosis. Experimental evaluation of nuclear segmentation ...
Jun 28, 2023 · The CNN Bi-path architecture was utilized to segment Pap smear images and classify cervical cancer, achieving substantial improvements in ...
Jan 25, 2018 · This paper addresses these limitations by proposing a method to directly classify cervical cells – without prior segmentation – based on deep.
Feb 13, 2023 · We proposed a robust DCNN for cervical cancer screening using whole-slide images (WSI) of ThinPrep cytologic test (TCT) slides from 211 cervical cancer and 189 ...