Copertina

On generalisability of segment anything model for nuclear instance segmentation in histology images

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xu, Kesi, Goetz, Lea, Rajpoot, Nasir
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Image and Video Processing Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Are foundation models efficient for medical image segmentation?
di: Ferreira, Danielle, et al.
Pubblicazione: (2023)

Synthesis of Annotated Colorectal Cancer Tissue Images from Gland Layout
di: Deshpande, Srijay, et al.
Pubblicazione: (2023)

Robust semi-automatic vessel tracing in the human retinal image by an instance segmentation neural network
di: Chen, Siyi, et al.
Pubblicazione: (2024)

Improving the generalization of deep learning models in the segmentation of mammography images
di: Hurtado, Jan, et al.
Pubblicazione: (2025)

High-resolution segmentations of the hypothalamus and its subregions for training of segmentation models
di: Rodrigues, Livia, et al.
Pubblicazione: (2024)

Shape-intensity knowledge distillation for robust medical image segmentation
di: Dong, Wenhui, et al.
Pubblicazione: (2024)

Switched auxiliary loss for robust training of transformer models for histopathological image segmentation
di: Hussain, Mustaffa, et al.
Pubblicazione: (2023)

Conditional diffusion model with spatial attention and latent embedding for medical image segmentation
di: Hejrati, Behzad, et al.
Pubblicazione: (2025)

Contour-weighted loss for class-imbalanced image segmentation
di: Huang, Zhhengyong, et al.
Pubblicazione: (2024)

HyperSpace: Hypernetworks for spacing-adaptive image segmentation
di: Joutard, Samuel, et al.
Pubblicazione: (2024)

Framework for lung CT image segmentation based on UNet++
di: Ziang, Hao, et al.
Pubblicazione: (2025)

A 3D generative model of pathological multi-modal MR images and segmentations
di: Fernandez, Virginia, et al.
Pubblicazione: (2023)

A Novel Approach to Linking Histology Images with DNA Methylation
di: Raza, Manahil, et al.
Pubblicazione: (2025)

A kinetic approach to consensus-based segmentation of biomedical images
di: Cabini, Raffaella Fiamma, et al.
Pubblicazione: (2022)

Improved Unet model for brain tumor image segmentation based on ASPP-coordinate attention mechanism
di: Wang, Zixuan, et al.
Pubblicazione: (2024)

UD-Mamba: A pixel-level uncertainty-driven Mamba model for medical image segmentation
di: Zhao, Weiren, et al.
Pubblicazione: (2025)

Crop and Couple: cardiac image segmentation using interlinked specialist networks
di: Khan, Abbas, et al.
Pubblicazione: (2024)

Deep mineralogical segmentation of thin section images based on QEMSCAN maps
di: de Mello, Jean Pablo Vieira, et al.
Pubblicazione: (2025)

In search of truth: Evaluating concordance of AI-based anatomy segmentation models
di: Giebeler, Lena, et al.
Pubblicazione: (2025)

Segment anything model (SAM) for brain extraction in fMRI studies
di: Chenna, Dwith, et al.
Pubblicazione: (2024)

Text-guided multi-stage cross-perception network for medical image segmentation
di: Chen, Gaoyu, et al.
Pubblicazione: (2025)

A hybrid approach for improving U-Net variants in medical image segmentation
di: Gupta, Aitik, et al.
Pubblicazione: (2023)

Lumbar spine segmentation in MR images: a dataset and a public benchmark
di: van der Graaf, Jasper W., et al.
Pubblicazione: (2023)

Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images
di: Soufi, Mazen, et al.
Pubblicazione: (2024)

In-context learning for medical image segmentation
di: Takaya, Eichi, et al.
Pubblicazione: (2024)

MOSformer: Momentum encoder-based inter-slice fusion transformer for medical image segmentation
di: Huang, De-Xing, et al.
Pubblicazione: (2024)

Blood vessel segmentation in en-face OCTA images: a frequency based method
di: Breger, Anna, et al.
Pubblicazione: (2021)

Synthetic magnetic resonance images for domain adaptation: Application to fetal brain tissue segmentation
di: de Dumast, Priscille, et al.
Pubblicazione: (2021)

Volumetric medical image segmentation through dual self-distillation in U-shaped networks
di: Banerjee, Soumyanil, et al.
Pubblicazione: (2023)

End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks
di: Kebaili, Aghiles, et al.
Pubblicazione: (2023)

Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation
di: Huang, Ling, et al.
Pubblicazione: (2023)

Generative augmentations for improved cardiac ultrasound segmentation using diffusion models
di: Van De Vyver, Gilles, et al.
Pubblicazione: (2025)

DmADs-Net: Dense multiscale attention and depth-supervised network for medical image segmentation
di: Fu, Zhaojin, et al.
Pubblicazione: (2024)

NUDF: Neural Unsigned Distance Fields for high resolution 3D medical image segmentation
di: Sørensen, Kristine, et al.
Pubblicazione: (2025)

Re-DiffiNet: Modeling discrepancies in tumor segmentation using diffusion models
di: Ren, Tianyi, et al.
Pubblicazione: (2024)

Rotterdam artery-vein segmentation (RAV) dataset
di: Quiros, Jose Vargas, et al.
Pubblicazione: (2025)

Dual Attention Model with Reinforcement Learning for Classification of Histology Whole-Slide Images
di: Raza, Manahil, et al.
Pubblicazione: (2023)

LiCAR: pseudo-RGB LiDAR image for CAR segmentation
di: Páez-Ubieta, Ignacio de Loyola, et al.
Pubblicazione: (2025)

Self-supervised learning improves robustness of deep learning lung tumor segmentation to CT imaging differences
di: Jiang, Jue, et al.
Pubblicazione: (2024)

Mobile U-ViT: Revisiting large kernel and U-shaped ViT for efficient medical image segmentation
di: Tang, Fenghe, et al.
Pubblicazione: (2025)