14.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Columbia UniversityUS16 papers
- Harvard UniversityUS13 papers
- Stanford UniversityUS12 papers
- Cornell UniversityUS11 papers
- National Institutes of HealthUS7 papers
- New York UniversityUS7 papers
- University of California, San FranciscoUS7 papers
- Emory UniversityUS6 papers
- Georgia Institute of TechnologyUS6 papers
- Hebrew University of JerusalemIL6 papers
- Imperial College LondonGB6 papers
- Mayo ClinicUS6 papers
12 papers · 1 filter
HeartBEiT: Vision Transformer for Electrocardiogram Data Improves Diagnostic Performance at Low Sample Sizes
Akhil Vaid, Joy Jiang, Ashwin Sawant +9
The electrocardiogram (ECG) is a ubiquitous diagnostic modality. Convolutional neural networks (CNNs) applied towards ECG analysis require large sample sizes, and transfer learning…
Novel structural-scale uncertainty measures and error retention curves: application to multiple sclerosis
Nataliia Molchanova, Vatsal Raina, Andrey Malinin +6
This paper focuses on the uncertainty estimation for white matter lesions (WML) segmentation in magnetic resonance imaging (MRI). On one side, voxel-scale segmentation errors cause…
Towards reliable calcification detection: calibration of uncertainty in coronary optical coherence tomography images
Hongshan Liu, Xueshen Li, Abdul Latif Bamba +4
Optical coherence tomography (OCT) has become increasingly essential in assisting the treatment of coronary artery disease (CAD). Image-guided solutions such as Percutaneous Corona…
Landmark Tracking in Liver US images Using Cascade Convolutional Neural Networks with Long Short-Term Memory
Yupei Zhang, Xianjin Dai, Zhen Tian +6
This study proposed a deep learning-based tracking method for ultrasound (US) image-guided radiation therapy. The proposed cascade deep learning model is composed of an attention n…
Analyzing Population-Level Trials as N-of-1 Trials: an Application to Gait
Lin Zhou, Juliana Schneider, Bert Arnrich +1
Studying individual causal effects of health interventions is of interest whenever intervention effects are heterogeneous between study participants. Conducting N-of-1 trials, whic…
Deformable Image Registration using Unsupervised Deep Learning for CBCT-guided Abdominal Radiotherapy
Huiqiao Xie, Yang Lei, Yabo Fu +6
CBCTs in image-guided radiotherapy provide crucial anatomy information for patient setup and plan evaluation. Longitudinal CBCT image registration could quantify the inter-fraction…
Multimodal Imaging-based Material Mass Density Estimation for Proton Therapy Using Physics-Constrained Deep Learning
Chih-Wei Chang, Raanan Marants, Yuan Gao +7
Mapping computed tomography (CT) number to material property dominates the proton range uncertainty. This work aims to develop a physics-constrained deep learning-based multimodal…
Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation
Josafat-Mattias Burmeister, Marcel Fernandez Rosas, Johannes Hagemann +5
Since labeling medical image data is a costly and labor-intensive process, active learning has gained much popularity in the medical image segmentation domain in recent years. A va…
Superconducting magnet designs and MRI accessibility: a review
Marina Manso Jimeno, John Thomas Vaughan, Sairam Geethanath
Presently, Magnetic Resonance Imaging (MRI) magnets must deliver excellent magnetic field (B0) uniformity to achieve optimum image quality. Long magnets can satisfy the homogeneity…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…
Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology
James M Dolezal, Andrew Srisuwananukorn, Dmitry Karpeyev +13
A model's ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are deployed into real-wo…
Mitigating Mismatch Compression in Differential Local Field Potentials
Vineet Tiruvadi, Sam James, Bryan Howell +9
Bidirectional deep brain stimulation (bdDBS) devices capable of recording differential local field potentials (dLFP) enable neural recordings alongside clinical therapy. Efforts to…