Luciano M. Prevedello
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View article: Standardizing Workflow, Patient Care, and Reimbursement for Radiology Second Opinions
Standardizing Workflow, Patient Care, and Reimbursement for Radiology Second Opinions Open
Second opinions in radiology are crucial for accurate diagnosis and patient management but often lack standardization, leading to inefficiencies and suboptimal reimbursement. We redesigned the second opinion workflow leveraging existing to…
View article: Incidental Pulmonary Nodule Detection and Factors Influencing Follow-Up: A Retrospective Study in an Academic Medical Center
Incidental Pulmonary Nodule Detection and Factors Influencing Follow-Up: A Retrospective Study in an Academic Medical Center Open
View article: The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset
The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset Open
The RSNA Abdominal Traumatic Injury CT (ie, RATIC) dataset contains 4274 abdominal CT studies with annotations related to traumatic injuries and is available at https://www.kaggle.com/competitions/rsna-2023-abdominal-trauma-detection and h…
View article: Growth dynamics of Rathke's Cleft cyst: a risk score system for surgical decision making
Growth dynamics of Rathke's Cleft cyst: a risk score system for surgical decision making Open
Objective Rathke's cleft cysts (RCCs) exhibit variable growth patterns, thus posing a challenge in predicting progression. While some RCCs may not cause symptoms, others can insidiously cause pituitary dysfunction, which is often irreversi…
View article: Assessing the Performance of Models from the 2022 RSNA Cervical Spine Fracture Detection Competition at a Level I Trauma Center
Assessing the Performance of Models from the 2022 RSNA Cervical Spine Fracture Detection Competition at a Level I Trauma Center Open
Winning machine learning models from the RSNA 2022 Cervical Spine Fracture Detection competition demonstrated high performance on a large clinical test set of emergency department cervical spine CT scans from a level I trauma center.
View article: Image segmentations produced by BAMF under the AIMI Annotations initiative
Image segmentations produced by BAMF under the AIMI Annotations initiative Open
The Imaging Data Commons (IDC)(https://imaging.datacommons.cancer.gov/) [1] connects researchers with publicly available cancer imaging data, often linked with other types of cancer data. Many of the collections have limited annotations du…
View article: Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts
Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts Open
The Radiological Society of North of America (RSNA) and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society have led a series of joint panels and seminars focused on the present impact and future directions of a…
View article: CT and MR utilization and morbidity metrics across Body Mass Index
CT and MR utilization and morbidity metrics across Body Mass Index Open
Objective Obesity is a high-morbidity chronic condition and risk factor for multiple diseases that necessitate imaging. This study assesses the relationship between BMI and same-year utilization of CT and MR imaging in a large healthcare p…
View article: The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset
The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset Open
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 includes 4,274 studies from 23 institutions across 14 countrie…
View article: Quantifying effects of blood pressure control on neuroimaging utilization in a large multi-institutional healthcare population
Quantifying effects of blood pressure control on neuroimaging utilization in a large multi-institutional healthcare population Open
Objectives Essential hypertension is a common chronic condition that can exacerbate or complicate various neurological diseases that may necessitate neuroimaging. Given growing medical imaging costs and the need to understand relationships…
View article: Erratum for: Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge
Erratum for: Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge Open
View article: Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges
Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges Open
The Radiological Society of North America (RSNA) has held artificial intelligence competitions to tackle real-world medical imaging problems at least annually since 2017. This article examines the challenges and processes involved in organ…
View article: The infundibulochiasmatic angle and the favorability of an endoscopic endonasal approach in type IV craniopharyngioma: illustrative case
The infundibulochiasmatic angle and the favorability of an endoscopic endonasal approach in type IV craniopharyngioma: illustrative case Open
BACKGROUND Lesions located in the floor of the third ventricle are among the most difficult to access in neurosurgery. The neurovascular structures can limit transcranial exposure, whereas tumor extension into the third ventricle can limit…
View article: Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge
Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge Open
Purpose To evaluate and report the performance of the winning algorithms of the Radiological Society of North America Cervical Spine Fracture AI Challenge. Materials and Methods The competition was open to the public on Kaggle from July 28…
View article: Data Liberation and Crowdsourcing in Medical Research: The Intersection of Collective and Artificial Intelligence
Data Liberation and Crowdsourcing in Medical Research: The Intersection of Collective and Artificial Intelligence Open
In spite of an exponential increase in the volume of medical data produced globally, much of these data are inaccessible to those who might best use them to develop improved health care solutions through the application of advanced analyti…
View article: A New Finding on Magnetic Resonance Imaging for Diagnosis of Hemifacial Spasm with High Accuracy and Interobserver Correlation
A New Finding on Magnetic Resonance Imaging for Diagnosis of Hemifacial Spasm with High Accuracy and Interobserver Correlation Open
Among patients with clinical hemifacial spasm (HFS), imaging exams aim to identify the neurovascular conflict (NVC) location. It has been proven that the identification in the preoperative exam increases the rate of surgical success. Despi…
View article: Detecting and Characterizing Inferior Vena Cava Filters on Abdominal Computed Tomography with Data-Driven Computational Frameworks
Detecting and Characterizing Inferior Vena Cava Filters on Abdominal Computed Tomography with Data-Driven Computational Frameworks Open
View article: The RSNA Cervical Spine Fracture CT Dataset
The RSNA Cervical Spine Fracture CT Dataset Open
This dataset is composed of cervical spine CT images with annotations related to fractures; it is available at https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/.
View article: Artificial Intelligence in Neuroradiology: A Review of Current Topics and Competition Challenges
Artificial Intelligence in Neuroradiology: A Review of Current Topics and Competition Challenges Open
There is an expanding body of literature that describes the application of deep learning and other machine learning and artificial intelligence methods with potential relevance to neuroradiology practice. In this article, we performed a li…
View article: An Artificial Intelligence Tool for Clinical Decision Support and Protocol Selection for Brain MRI
An Artificial Intelligence Tool for Clinical Decision Support and Protocol Selection for Brain MRI Open
Our model achieved high accuracy on a standard based on physician consensus. It showed promise as a clinical decision support tool to reduce the workload by automating the protocolling of a sizeable portion of examinations while maintainin…
View article: Prediction of Model Generalizability for Unseen Data: Methodology and Case Study in Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI
Prediction of Model Generalizability for Unseen Data: Methodology and Case Study in Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI Open
A medical AI system's generalizability describes the continuity of its performance acquired from varying geographic, historical, and methodologic settings. Previous literature on this topic has mostly focused on "how" to achieve high gener…
View article: Virtual CT Myelography: A Patch-Based Machine Learning Model to Improve Intraspinal Soft Tissue Visualization on Unenhanced Dual-Energy Lumbar Spine CT
Virtual CT Myelography: A Patch-Based Machine Learning Model to Improve Intraspinal Soft Tissue Visualization on Unenhanced Dual-Energy Lumbar Spine CT Open
Background: Distinguishing between the spinal cord and cerebrospinal fluid (CSF) non-invasively on CT is challenging due to their similar mass densities. We hypothesize that patch-based machine learning applied to dual-energy CT can accura…
View article: Advancing Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI Using Noisy Student-Based Training
Advancing Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI Using Noisy Student-Based Training Open
The detection of brain metastases (BM) in their early stages could have a positive impact on the outcome of cancer patients. The authors previously developed a framework for detecting small BM (with diameters of 10%) were also observed in …
View article: Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features
Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features Open
The emergence of the COVID-19 pandemic over a relatively brief interval illustrates the need for rapid data-driven approaches to facilitate clinical decision making. We examined a machine learning process to predict inpatient mortality amo…
View article: Advancing Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI using Noisy Student-based Training
Advancing Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI using Noisy Student-based Training Open
The detection of brain metastases (BM) in their early stages could have a positive impact on the outcome of cancer patients. We previously developed a framework for detecting small BM (with diameters of less than 15mm) in T1-weighted Contr…
View article: Training Strategies for Radiology Deep Learning Models in Data-limited Scenarios
Training Strategies for Radiology Deep Learning Models in Data-limited Scenarios Open
Data-driven approaches have great potential to shape future practices in radiology. The most straightforward strategy to obtain clinically accurate models is to use large, well-curated and annotated datasets. However, patient privacy const…
View article: The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification Open
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), and the Medical Image Computing and Computer Assisted Int…
View article: Augmented Networks for Faster Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI
Augmented Networks for Faster Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI Open
Early detection of brain metastases (BM) is one of the determining factors for the successful treatment of patients with cancer; however, the accurate detection of small BM lesions (< 15mm) remains a challenging task. We previously describ…
View article: Natural Language Processing of Radiology Text Reports: Interactive Text Classification
Natural Language Processing of Radiology Text Reports: Interactive Text Classification Open
This report presents a hands-on introduction to natural language processing (NLP) of radiology reports with deep neural networks in Google Colaboratory (Colab) to introduce readers to the rapidly evolving field of NLP. The implementation o…
View article: Constrained generative adversarial network ensembles for sharable synthetic medical images
Constrained generative adversarial network ensembles for sharable synthetic medical images Open
Purpose: Sharing medical images between institutions, or even inside the same institution, is restricted by various laws and regulations; research projects requiring large datasets may suffer as a result. These limitations might be …