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Found 10 papers, 2 papers with code
Estimation and Analysis of Slice Propagation Uncertainty in 3D Anatomy Segmentation
This limitation has led to a growing interest in self-supervised approaches in tandem with the abundance of available un-annotated data.
StainDiffuser: MultiTask Dual Diffusion Model for Virtual Staining
Hematoxylin and Eosin (H&E) staining is the most commonly used for disease diagnosis and tumor recurrence tracking.
EfficientMorph: Parameter-Efficient Transformer-Based Architecture for 3D Image Registration
Secondly, feature similarities across attention heads that were recently found in multi-head attention architectures indicate a significant computational redundancy, suggesting that the capacity of the network could be better utilized to enhance performance.
Ranked #1 on
Medical Image Registration
on OASIS
(val dsc metric)
MASSM: An End-to-End Deep Learning Framework for Multi-Anatomy Statistical Shape Modeling Directly From Images
Statistical Shape Modeling (SSM) is an effective method for quantitatively analyzing anatomical variations within populations.
Multi-Set Inoculation: Assessing Model Robustness Across Multiple Challenge Sets
Language models, given their black-box nature, often exhibit sensitivity to input perturbations, leading to trust issues due to hallucinations.
Structural Cycle GAN for Virtual Immunohistochemistry Staining of Gland Markers in the Colon
Quantitative metrics such as FID and SSIM are frequently used for the analysis of generative models, but they do not correlate explicitly with higher-quality virtual staining results.
To pretrain or not to pretrain? A case study of domain-specific pretraining for semantic segmentation in histopathology
In this study, we compare the performance of gland and cell segmentation tasks with histopathology domain-specific and non-domain-specific (real-world images) pretrained weights.
ADASSM: Adversarial Data Augmentation in Statistical Shape Models From Images
However, these augmentation methods focus on shape augmentation, whereas deep learning models exhibit image-based texture bias resulting in sub-optimal models.
InfoSync: Information Synchronization across Multilingual Semi-structured Tables
The proposed method includes 1) Information Alignment to map rows and 2) Information Update for updating missing/outdated information for aligned tables across multilingual tables.
Unsupervised Domain Adaptation for Medical Image Segmentation via Feature-space Density Matching
Nonetheless, they often fail to generalize when there is a significant domain (i. e., distributional) shift between the training (i. e., source) data and the dataset(s) encountered when deployed (i. e., target), necessitating manual annotations for the target data to achieve acceptable performance.
