no code implementations • 21 Nov 2023 • Ken C. L. Wong, Levente Klein, Ademir Ferreira da Silva, Hongzhi Wang, Jitendra Singh, Tanveer Syeda-Mahmood
To study the use of CNNs on SOC remote sensing, here we propose the FNO-DenseNet based on the Fourier neural operator (FNO).
1 code implementation • 5 Oct 2023 • Ken C. L. Wong, Hongzhi Wang, Tanveer Syeda-Mahmood
With the introduction of Transformers, different attention-based models have been proposed for image segmentation with promising results.
1 code implementation • 5 Oct 2023 • Ken C. L. Wong, Hongzhi Wang, Tanveer Syeda-Mahmood
Due to the computational complexity of 3D medical image segmentation, training with downsampled images is a common remedy for out-of-memory errors in deep learning.
1 code implementation • 10 Jan 2022 • Ken C. L. Wong, Mehdi Moradi
For existing loss functions for multi-class image segmentation, there is usually a tradeoff among accuracy, robustness to hyperparameters, and manual weight selections for combining different losses.
no code implementations • 10 Dec 2021 • Ken C. L. Wong, Hongzhi Wang, Etienne E. Vos, Bianca Zadrozny, Campbell D. Watson, Tanveer Syeda-Mahmood
Global warming leads to the increase in frequency and intensity of climate extremes that cause tremendous loss of lives and property.
no code implementations • 6 Aug 2021 • Ken C. L. Wong, Satyananda Kashyap, Mehdi Moradi
Network-based transfer learning allows the reuse of deep learning features with limited data, but the resulting models can be unnecessarily large.
no code implementations • 23 Mar 2021 • Ken C. L. Wong, Elena S. Sinkovskaya, Alfred Z. Abuhamad, Tanveer Syeda-Mahmood
Congenital heart disease (CHD) is the most common congenital abnormality associated with birth defects in the United States.
no code implementations • 22 Mar 2021 • Ken C. L. Wong, Satyananda Kashyap, Mehdi Moradi
By imposing L1 regularization and thresholding on the scaling weights, this framework iteratively removes unnecessary feature channels from a pre-trained model.
no code implementations • 2 Aug 2020 • Satyananda Kashyap, Alexandros Karargyris, Joy Wu, Yaniv Gur, Arjun Sharma, Ken C. L. Wong, Mehdi Moradi, Tanveer Syeda-Mahmood
Deep learning has now become the de facto approach to the recognition of anomalies in medical imaging.
no code implementations • 27 Jul 2020 • Tanveer Syeda-Mahmood, Ken C. L. Wong, Yaniv Gur, Joy T. Wu, Ashutosh Jadhav, Satyananda Kashyap, Alexandros Karargyris, Anup Pillai, Arjun Sharma, Ali Bin Syed, Orest Boyko, Mehdi Moradi
Obtaining automated preliminary read reports for common exams such as chest X-rays will expedite clinical workflows and improve operational efficiencies in hospitals.
no code implementations • 12 Sep 2019 • Ken C. L. Wong, Mehdi Moradi
Deep learning has largely reduced the need for manual feature selection in image segmentation.
no code implementations • 2 Jul 2019 • Vaishnavi Subramanian, Hongzhi Wang, Joy T. Wu, Ken C. L. Wong, Arjun Sharma, Tanveer Syeda-Mahmood
Central venous catheters (CVCs) are commonly used in critical care settings for monitoring body functions and administering medications.
no code implementations • 21 Jun 2019 • Alexandros Karargyris, Ken C. L. Wong, Joy T. Wu, Mehdi Moradi, Tanveer Syeda-Mahmood
We experiment with two different deep neural network architectures and show that the proposed method results in a large improvement in the performance of the classifiers, specially on negated findings.
no code implementations • 21 Jun 2019 • Tanveer Syeda-Mahmood, Hassan M. Ahmad, Nadeem Ansari, Yaniv Gur, Satyananda Kashyap, Alexandros Karargyris, Mehdi Moradi, Anup Pillai, Karthik Sheshadri, Wei-Ting Wang, Ken C. L. Wong, Joy T. Wu
Chest X-rays are the most common diagnostic exams in emergency rooms and hospitals.
no code implementations • 2 Apr 2019 • Ken C. L. Wong, Mehdi Moradi, Joy Wu, Tanveer Syeda-Mahmood
In this work, we report a deep neural network trained for classifying CXRs with the goal of identifying a large number of normal (disease-free) images without risking the discharge of sick patients.
1 code implementation • 31 Aug 2018 • Ken C. L. Wong, Mehdi Moradi, Hui Tang, Tanveer Syeda-Mahmood
In this paper, we propose a network architecture and the corresponding loss function which improve segmentation of very small structures.
no code implementations • 15 Aug 2018 • Ken C. L. Wong, Tanveer Syeda-Mahmood, Mehdi Moradi
Deep learning has shown promising results in medical image analysis, however, the lack of very large annotated datasets confines its full potential.
no code implementations • 7 May 2018 • Ken C. L. Wong, Alexandros Karargyris, Tanveer Syeda-Mahmood, Mehdi Moradi
We train a discriminative segmentation model only on normal images to provide a source of knowledge to be transferred to a disease detection classifier.