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20182022
most citedChest ImaGenome Dataset for Clinical Reasoning

26 citations · 55 across the 9 of their papers we have counts for

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5 papers · 1 filter

eess.IV2022★ 6 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…

eess.IV2022

3D Segmentation with Fully Trainable Gabor Kernels and Pearson's Correlation Coefficient

Ken C. L. Wong, Mehdi Moradi

The convolutional layer and loss function are two fundamental components in deep learning. Because of the success of conventional deep learning kernels, the less versatile Gabor ke…

eess.IV2020

Learning Invariant Feature Representation to Improve Generalization across Chest X-ray Datasets

Sandesh Ghimire, Satyananda Kashyap, Joy T. Wu +2

Chest radiography is the most common medical image examination for screening and diagnosis in hospitals. Automatic interpretation of chest X-rays at the level of an entry-level rad…

eess.IV2020

A robust network architecture to detect normal chest X-ray radiographs

Ken C. L. Wong, Mehdi Moradi, Joy Wu +10

We propose a novel deep neural network architecture for normalcy detection in chest X-ray images. This architecture treats the problem as fine-grained binary classification in whic…

eess.IV2019

SegNAS3D: Network Architecture Search with Derivative-Free Global Optimization for 3D Image Segmentation

Ken C. L. Wong, Mehdi Moradi

Deep learning has largely reduced the need for manual feature selection in image segmentation. Nevertheless, network architecture optimization and hyperparameter tuning are mostly…