Search Results for author:
Found 9 papers, 0 papers with code
Integrating multiscale topology in digital pathology with pyramidal graph convolutional networks
The architecture's unique configuration allows for the concurrent modeling of structural patterns at lower magnifications and detailed cellular features at higher ones, while also quantifying the contribution of each magnification level to the prediction.
The Importance of Downstream Networks in Digital Pathology Foundation Models
Digital pathology has significantly advanced disease detection and pathologist efficiency through the analysis of gigapixel whole-slide images (WSI).
A comparative study between vision transformers and CNNs in digital pathology
Due to the sparse availability of annotated whole slide images, we further compared both models pretrained on large amounts of unlabeled whole-slide images using state-of-the-art self-supervised approaches.
XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms
Moreover, the improvement in utilizing synthetic images for augmenting the real data is evident through the reduction of Hausdorff distance up to 28% and an increase in the Dice score up to 5%, indicating a higher similarity to the ground truth in all dimensions.
Risk of Training Diagnostic Algorithms on Data with Demographic Bias
Surprisingly, we found that papers focusing on diagnosis rarely describe the demographics of the datasets used, and the diagnosis is purely based on images.
4D Semantic Cardiac Magnetic Resonance Image Synthesis on XCAT Anatomical Model
Using the parameterized motion model of the XCAT heart, we generate labels for 25 time frames of the heart for one cardiac cycle at 18 locations for the short axis view.
Retrieving challenging vessel connections in retinal images by line co-occurrence statistics
We propose to find line co-occurrence statistics from the centerlines of blood vessels in retinal images and show its remarkable similarity to a well-known probabilistic model for the connectivity pattern in the primary visual cortex.
Curvature Integration in a 5D Kernel for Extracting Vessel Connections in Retinal Images
Tree-like structures such as retinal images are widely studied in computer-aided diagnosis systems for large-scale screening programs.
Analysis of Vessel Connectivities in Retinal Images by Cortically Inspired Spectral Clustering
These signs can be investigated based on microaneurysms or smaller vessels.
