activity
20172023
most citedDomain-adversarial neural networks to address the appearance variability of histopathology images

1.1k citations · 1.5k across the 18 of their papers we have counts for

collaborators

25 papers

eess.IV20237 cited

Image-Based Soil Organic Carbon Remote Sensing from Satellite Images with Fourier Neural Operator and Structural Similarity

Ken C. L. Wong, Levente Klein, Ademir Ferreira da Silva +3

Soil organic carbon (SOC) sequestration is the transfer and storage of atmospheric carbon dioxide in soils, which plays an important role in climate change mitigation. SOC concentr…

eess.IV20226 cited

Towards Automatic Prediction of Outcome in Treatment of Cerebral Aneurysms

Ashutosh Jadhav, Satyananda Kashyap, Hakan Bulu +6

Intrasaccular flow disruptors treat cerebral aneurysms by diverting the blood flow from the aneurysm sac. Residual flow into the sac after the intervention is a failure that could…

cs.LG20226 cited

Fusing Modalities by Multiplexed Graph Neural Networks for Outcome Prediction in Tuberculosis

Niharika S. D'Souza, Hongzhi Wang, Andrea Giovannini +4

In a complex disease such as tuberculosis, the evidence for the disease and its evolution may be present in multiple modalities such as clinical, genomic, or imaging data. Effectiv…

eess.IV2022

Spatially-Preserving Flattening for Location-Aware Classification of Findings in Chest X-Rays

Neha Srivathsa, Razi Mahmood, Tanveer Syeda-Mahmood

Chest X-rays have become the focus of vigorous deep learning research in recent years due to the availability of large labeled datasets. While classification of anomalous findings…

eess.IV20215 cited

Multiview and Multiclass Image Segmentation using Deep Learning in Fetal Echocardiography

Ken C. L. Wong, Elena S. Sinkovskaya, Alfred Z. Abuhamad +1

Congenital heart disease (CHD) is the most common congenital abnormality associated with birth defects in the United States. Despite training efforts and substantial advancement in…

cs.LG2021

Multimodal fusion using sparse CCA for breast cancer survival prediction

Vaishnavi Subramanian, Tanveer Syeda-Mahmood, Minh N. Do

Effective understanding of a disease such as cancer requires fusing multiple sources of information captured across physical scales by multimodal data. In this work, we propose a n…