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
Vision Language Models versus Machine Learning Models Performance on Polyp Detection and Classification in Colonoscopy Images
Mohammad Amin Khalafi, Seyed Amir Ahmad Safavi-Naini, Ameneh Salehi +13
Introduction: This study provides a comprehensive performance assessment of vision-language models (VLMs) against established convolutional neural networks (CNNs) and classic machi…
X-ray2CTPA: Leveraging Diffusion Models to Enhance Pulmonary Embolism Classification
Noa Cahan, Eyal Klang, Galit Aviram +4
Chest X-rays or chest radiography (CXR), commonly used for medical diagnostics, typically enables limited imaging compared to computed tomography (CT) scans, which offer more detai…
VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification
Zelong Liu, Andrew Tieu, Nikhil Patel +9
Artificial Intelligence (AI) has the potential to revolutionize diagnosis and segmentation in medical imaging. However, development and clinical implementation face multiple challe…
MRAnnotator: multi-Anatomy and many-Sequence MRI segmentation of 44 structures
Alexander Zhou, Zelong Liu, Andrew Tieu +16
In this retrospective study, we annotated 44 structures on two datasets: an internal dataset of 1,518 MRI sequences from 843 patients at the Mount Sinai Health System, and an exter…
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…
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…
The Federated Tumor Segmentation (FeTS) Challenge
Sarthak Pati, Ujjwal Baid, Maximilian Zenk +29
This manuscript describes the first challenge on Federated Learning, namely the Federated Tumor Segmentation (FeTS) challenge 2021. International challenges have become the standar…
Automatic Brain Tumor Segmentation with Scale Attention Network
Yading Yuan
Automatic segmentation of brain tumors is an essential but challenging step for extracting quantitative imaging biomarkers for accurate tumor detection, diagnosis, prognosis, treat…
Enhancing high-content imaging for studying microtubule networks at large-scale
Hao-Chih Lee, Sarah T Cherng, Riccardo Miotto +1
Given the crucial role of microtubules for cell survival, many researchers have found success using microtubule-targeting agents in the search for effective cancer therapeutics. Un…
A Deep Regression Model for Seed Identification in Prostate Brachytherapy
Yading Yuan, Ren-Dih Sheu, Luke Fu +1
Post-implant dosimetry (PID) is an essential step of prostate brachytherapy that utilizes CT to image the prostate and allow the location and dose distribution of the radioactive s…
Free-breathing and ungated cardiac cine using navigator-less spiral SToRM
Abdul Haseeb Ahmed, Ruixi Zhou, Yang Yang +3
We introduce a kernel low-rank algorithm to recover free-breathing and ungated dynamic MRI from spiral acquisitions without explicit k-space navigators. It is often challenging for…