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Found 6 papers, 4 papers with code
Practical Guidelines for Cell Segmentation Models Under Optical Aberrations in Microscopy
By simulating different types of aberrations, including astigmatism, coma, spherical aberration, trefoil, and mixed aberrations, we conduct a thorough evaluation of various cell instance segmentation models using the DynamicNuclearNet (DNN) and LIVECell datasets, representing fluorescence and bright field microscopy cell datasets, respectively.
DEFN: Dual-Encoder Fourier Group Harmonics Network for Three-Dimensional Indistinct-Boundary Object Segmentation
The precise spatial and quantitative delineation of indistinct-boundary medical objects is paramount for the accuracy of diagnostic protocols, efficacy of surgical interventions, and reliability of postoperative assessments.
Structure-aware scale-adaptive networks for cancer segmentation in whole-slide images
Cancer segmentation in whole-slide images is a fundamental step for viable tumour burden estimation, which is of great value for cancer assessment.
Magnification-independent Histopathological Image Classification with Similarity-based Multi-scale Embeddings
Experimental results show that the SMSE improves the performance for histopathological image classification tasks for both breast and liver cancers by a large margin compared to previous methods.
Histopathological Image Classification
Image Classification
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SRPN: similarity-based region proposal networks for nuclei and cells detection in histology images
The embedding layer is added into the region proposal networks, enabling the networks to learn discriminative features based on similarity learning.
GAN-based Virtual Re-Staining: A Promising Solution for Whole Slide Image Analysis
We proposed a conditional CycleGAN (cCGAN) network to transform the H\&E stained images into IHC stained images, facilitating virtual IHC staining on the same slide.
