585 citations · 755 across the 14 of their papers we have counts for
16 papers
The RSNA Intracranial Aneurysm (RSNA-ICA) Dataset
Maria Correia de Verdier, Rachit Saluja, Jason Sho +37
Intracranial aneurysm rupture is associated with substantial morbidity and mortality, yet aneurysm detection remains challenging, particularly for small lesions and on routine non-…
RSNA Large Language Model Benchmark Dataset for Chest Radiographs of Cardiothoracic Disease: Radiologist Evaluation and Validation Enhanced by AI Labels (REVEAL-CXR)
Yishu Wei, Adam E. Flanders, Errol Colak +35
Multimodal large language models have demonstrated comparable performance to that of radiology trainees on multiple-choice board-style exams. However, to develop clinically useful…
A Multi-agent Large Language Model Framework to Automatically Assess Performance of a Clinical AI Triage Tool
Adam E. Flanders, Yifan Peng, Luciano Prevedello +6
Purpose: The purpose of this study was to determine if an ensemble of multiple LLM agents could be used collectively to provide a more reliable assessment of a pixel-based AI triag…
The RSNA Lumbar Degenerative Imaging Spine Classification (LumbarDISC) Dataset
Tyler J. Richards, Adam E. Flanders, Errol Colak +33
The Radiological Society of North America (RSNA) Lumbar Degenerative Imaging Spine Classification (LumbarDISC) dataset is the largest publicly available dataset of adult MRI lumbar…
The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset
Jeffrey D. Rudie, Hui-Ming Lin, Robyn L. Ball +37
The RSNA Abdominal Traumatic Injury CT (RATIC) dataset is the largest publicly available collection of adult abdominal CT studies annotated for traumatic injuries. This dataset inc…
The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting
Florian Kofler, Felix Meissen, Felix Steinbauer +103
A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition ti…
AI Models Close to your Chest: Robust Federated Learning Strategies for Multi-site CT
Edward H. Lee, Brendan Kelly, Emre Altinmakas +27
While it is well known that population differences from genetics, sex, race, and environmental factors contribute to disease, AI studies in medicine have largely focused on locoreg…
BenchMD: A Benchmark for Unified Learning on Medical Images and Sensors
Kathryn Wantlin, Chenwei Wu, Shih-Cheng Huang +12
Medical data poses a daunting challenge for AI algorithms: it exists in many different modalities, experiences frequent distribution shifts, and suffers from a scarcity of examples…
NanoBatch Privacy: Enabling fast Differentially Private learning on the IPU
Edward H. Lee, Mario Michael Krell, Alexander Tsyplikhin +3
Differentially private SGD (DPSGD) has recently shown promise in deep learning. However, compared to non-private SGD, the DPSGD algorithm places computational overheads that can un…
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
Ujjwal Baid, Satyam Ghodasara, Suyash Mohan +100
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR)…
A Real-World Demonstration of Machine Learning Generalizability: Intracranial Hemorrhage Detection on Head CT
Hojjat Salehinejad, Jumpei Kitamura, Noah Ditkofsky +7
Machine learning (ML) holds great promise in transforming healthcare. While published studies have shown the utility of ML models in interpreting medical imaging examinations, thes…
Deep Sequential Learning for Cervical Spine Fracture Detection on Computed Tomography Imaging
Hojjat Salehinejad, Edward Ho, Hui-Ming Lin +10
Fractures of the cervical spine are a medical emergency and may lead to permanent paralysis and even death. Accurate diagnosis in patients with suspected fractures by computed tomo…
Cylindrical Transform: 3D Semantic Segmentation of Kidneys With Limited Annotated Images
Hojjat Salehinejad, Sumeya Naqvi, Errol Colak +2
In this paper, we propose a novel technique for sampling sequential images using a cylindrical transform in a cylindrical coordinate system for kidney semantic segmentation in abdo…
Recent Advances in Recurrent Neural Networks
Hojjat Salehinejad, Sharan Sankar, Joseph Barfett +2
Recurrent neural networks (RNNs) are capable of learning features and long term dependencies from sequential and time-series data. The RNNs have a stack of non-linear units where a…
Interpretation of Mammogram and Chest X-Ray Reports Using Deep Neural Networks - Preliminary Results
Hojjat Salehinejad, Shahrokh Valaee, Aren Mnatzakanian +3
Radiology reports are an important means of communication between radiologists and other physicians. These reports express a radiologist's interpretation of a medical imaging exami…
A Convolutional Neural Network for Search Term Detection
Hojjat Salehinejad, Joseph Barfett, Parham Aarabi +4
Pathfinding in hospitals is challenging for patients, visitors, and even employees. Many people have experienced getting lost due to lack of clear guidance, large footprint of hosp…