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20182022
most cited3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes

207 citations · 321 across the 12 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

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…

eess.IV2019

Automated Detection and Type Classification of Central Venous Catheters in Chest X-Rays

Vaishnavi Subramanian, Hongzhi Wang, Joy T. Wu +3

Central venous catheters (CVCs) are commonly used in critical care settings for monitoring body functions and administering medications. They are often described in radiology repor…

eess.IV2019

Boosting the rule-out accuracy of deep disease detection using class weight modifiers

Alexandros Karargyris, Ken C. L. Wong, Joy T. Wu +2

In many screening applications, the primary goal of a radiologist or assisting artificial intelligence is to rule out certain findings. The classifiers built for such applications…

cs.CV2019★ 1 cited

Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-rays

Tanveer Syeda-Mahmood, Hassan M. Ahmad, Nadeem Ansari +9

Chest X-rays are the most common diagnostic exams in emergency rooms and hospitals. There has been a surge of work on automatic interpretation of chest X-rays using deep learning a…

cs.CV2019★ 6 cited

Identifying disease-free chest X-ray images with deep transfer learning

Ken C. L. Wong, Mehdi Moradi, Joy Wu +1

Chest X-rays (CXRs) are among the most commonly used medical image modalities. They are mostly used for screening, and an indication of disease typically results in subsequent test…