activity
20212024
most citedhist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology images

63 citations · 108 across the 9 of their papers we have counts for

collaborators
Showing eess.IVShow all

5 papers · 1 filter

eess.IV2024

LMBF-Net: A Lightweight Multipath Bidirectional Focal Attention Network for Multifeatures Segmentation

Tariq M Khan, Shahzaib Iqbal, Syed S. Naqvi +2

Retinal diseases can cause irreversible vision loss in both eyes if not diagnosed and treated early. Since retinal diseases are so complicated, retinal imaging is likely to show tw…

eess.IV2024

Semi-supervised variational autoencoder for cell feature extraction in multiplexed immunofluorescence images

Piumi Sandarenu, Julia Chen, Iveta Slapetova +6

Advancements in digital imaging technologies have sparked increased interest in using multiplexed immunofluorescence (mIF) images to visualise and identify the interactions between…

eess.IV2023

Feature Enhancer Segmentation Network (FES-Net) for Vessel Segmentation

Tariq M. Khan, Muhammad Arsalan, Shahzaib Iqbal +2

Diseases such as diabetic retinopathy and age-related macular degeneration pose a significant risk to vision, highlighting the importance of precise segmentation of retinal vessels…

eess.IV20235 cited

Hybrid Dual Mean-Teacher Network With Double-Uncertainty Guidance for Semi-Supervised Segmentation of MRI Scans

Jiayi Zhu, Bart Bolsterlee, Brian V. Y. Chow +2

Semi-supervised learning has made significant progress in medical image segmentation. However, existing methods primarily utilize information acquired from a single dimensionality…

eess.IV20211 cited

Leveraging Image Complexity in Macro-Level Neural Network Design for Medical Image Segmentation

Tariq M. Khan, Syed S. Naqvi, Erik Meijering

Recent progress in encoder-decoder neural network architecture design has led to significant performance improvements in a wide range of medical image segmentation tasks. However,…