31 citations · 86 across the 8 of their papers we have counts for
9 papers
Integrating multiscale topology in digital pathology with pyramidal graph convolutional networks
Victor Ibañez, Przemyslaw Szostak, Quincy Wong +3
Graph convolutional networks (GCNs) have emerged as a powerful alternative to multiple instance learning with convolutional neural networks in digital pathology, offering superior…
The Importance of Downstream Networks in Digital Pathology Foundation Models
Gustav Bredell, Marcel Fischer, Przemyslaw Szostak +2
Digital pathology has significantly advanced disease detection and pathologist efficiency through the analysis of gigapixel whole-slide images (WSI). In this process, WSIs are firs…
A comparative study between vision transformers and CNNs in digital pathology
Luca Deininger, Bernhard Stimpel, Anil Yuce +5
Recently, vision transformers were shown to be capable of outperforming convolutional neural networks when pretrained on sufficient amounts of data. In comparison to convolutional…
XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms
Sina Amirrajab, Samaneh Abbasi-Sureshjani, Yasmina Al Khalil +4
Generative adversarial networks (GANs) have provided promising data enrichment solutions by synthesizing high-fidelity images. However, generating large sets of labeled images with…
Risk of Training Diagnostic Algorithms on Data with Demographic Bias
Samaneh Abbasi-Sureshjani, Ralf Raumanns, Britt E. J. Michels +2
One of the critical challenges in machine learning applications is to have fair predictions. There are numerous recent examples in various domains that convincingly show that algor…
4D Semantic Cardiac Magnetic Resonance Image Synthesis on XCAT Anatomical Model
Samaneh Abbasi-Sureshjani, Sina Amirrajab, Cristian Lorenz +3
We propose a hybrid controllable image generation method to synthesize anatomically meaningful 3D+t labeled Cardiac Magnetic Resonance (CMR) images. Our hybrid method takes the mec…
Retrieving challenging vessel connections in retinal images by line co-occurrence statistics
Samaneh Abbasi-Sureshjani, Jiong Zhang, Remco Duits +1
Natural images contain often curvilinear structures, which might be disconnected, or partly occluded. Recovering the missing connection of disconnected structures is an open issue…
Curvature Integration in a 5D Kernel for Extracting Vessel Connections in Retinal Images
Samaneh Abbasi-Sureshjani, Marta Favali, Giovanna Citti +2
Tree-like structures such as retinal images are widely studied in computer-aided diagnosis systems for large-scale screening programs. Despite several segmentation and tracking met…
Analysis of Vessel Connectivities in Retinal Images by Cortically Inspired Spectral Clustering
Marta Favali, Samaneh Abbasi-Sureshjani, Bart ter Haar Romeny +1
Retinal images provide early signs of diabetic retinopathy, glaucoma, and hypertension. These signs can be investigated based on microaneurysms or smaller vessels. The diagnostic b…