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36 results for “contrast-enhanced mammography”
Dataset related to article "Performance of dual-energy subtraction in contrast-enhanced mammography for three different manufacturers: a phantom study"
<p><span>The dataset provided here contains the raw data used in the study discussed in this article. The primary objective of the study was to conduct a comparative analysis of the performance of dual energy subtraction (DES) images acquired using contrast-enhanced mammography (CEM) systems produced by three different manufacturers. The comparison, facilitated by a CEM-specific phantom, focused on the assessment of radiation dose and image quality.</span></p> <p><span>Composed of three separate CSV files, the dataset is structured as follows:</span></p> <p><span>1) "Dose-related data": This file provides exposure parameters (including A/F combination, tube voltage and exposure) and the corresponding mean glandular dose (MGD for low-energy (LE) and high-energy (HE) images. Data are given for each CEM system and automatic exposure mode (AEC).</span></p> <p><span>2) "CNR-related data": Encapsulated in this file are data extracted from the phantom DES images. These include measurements of the mean pixel value (MPV) for each iodinated contrast detail, as well as the MPV and standard deviation (SD) for the surrounding background. These data were used to calculate the contrast-to-noise ratio (CNR) for the iodinated contrast details.</span></p> <p><span>3) “Residual CNR data”: This file includes MPV and SD data extracted from phantom DES images, which were useful for calculating the residual CNR after cancellation of the normal background tissue by the DES algorithm.</span></p>
Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to detect breast malignant Lesions
<p>We uploade the dataset of the manuscript "Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to detect breast malignant Lesions" by Current Oncology.</p> <p> </p>
Screening Contrast-Enhanced Mammography as an Alternative to MRI
ClinicalTrials.gov study NCT04764292. IPD Sharing: YES. Countries: 1. Publications: 1.
Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography
<p>I uploaded the database of the extracted features for each enrolled patient in the manuscript "Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography" to evaluate radiomic features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptor; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer.</p>
Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification
<p>We uploaded the dataset of included patients of manuscript: Petrillo A, Fusco R, Vallone P, Filice S, Granata V, Petrosino T, Rosaria Rubulotta M, Setola SV, Mattace Raso M, Maio F, Raiano C, Siani C, Di Bonito M, Botti G. Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification. Breast J. 2020 May;26(5):860-872. doi: 10.1111/tbj.13739. Epub 2019 Dec 30. PMID: 31886607.</p>
Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification.
<p>We uploaded the database of 104 lesions included in the manuscript: Fusco R, Piccirillo A, Sansone M, Granata V, Rubulotta MR, Petrosino T, Barretta ML, Vallone P, Di Giacomo R, Esposito E, Di Bonito M, Petrillo A. Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification. Diagnostics (Basel). 2021 Apr 30;11(5):815. doi: 10.3390/diagnostics11050815. PMID: 33946333; PMCID: PMC8146084.</p>
Dual-energy Contrast-enhanced (2D and 3D Mammography Versus Contrast-enhanced MRI)- A Pilot Study
ClinicalTrials.gov study NCT01433640. IPD Sharing: Not stated. Countries: 1. Publications: 9.
Prediction of Breast Cancer Histological Outcome with Radiomics and Artificial Intelligence Analysis by Contrast-Enhanced Mammography
<p>Radiomic features on contrast-enhanced mammography (CEM) images</p>
Prospective Case Collection Study of Contrast-Enhanced Mammography Imaging Acquired on a New Investigational Device
ClinicalTrials.gov study NCT06636539. IPD Sharing: NO. Countries: 1. Publications: 0.
Performance of Contrast-Enhanced Spectral Mammography to Assess Neoadjuvant Chemotherapy Response (CEDM)
ClinicalTrials.gov study NCT04625517. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Can Contrast-Enhanced Spectral Mammography Improve the Accuracy of a Diagnosis
ClinicalTrials.gov study NCT03929822. IPD Sharing: YES. Countries: 1. Publications: 0.
Study of Dual-energy (DE) Contrast-enhanced (CE) Digital Mammography
ClinicalTrials.gov study NCT02995980. IPD Sharing: NO. Countries: 1. Publications: 0.
Contrast-Enhanced Mammography for Breast Cancer Staging in Patients Referred for a Second Opinion
ClinicalTrials.gov study NCT05036083. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Contrast-Enhanced Digital Mammography (CEDM) for Identifying a Change in Management of Women With Newly Diagnosed Breast Cancer
ClinicalTrials.gov study NCT01303419. IPD Sharing: Not stated. Countries: 5. Publications: 0.
An Imaging Technology, Contrast-Enhanced Mammography, in Predicting Breast Cancer
ClinicalTrials.gov study NCT04871139. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Contrast-Enhanced Spectral Mammography (CESM)
ClinicalTrials.gov study NCT06311695. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study of Contrast-Enhanced Mammography (CEM) Scans in People With Breast Cancer
ClinicalTrials.gov study NCT05990478. IPD Sharing: YES. Countries: 0. Publications: 0.
From Variability to Standardization: The Impact of Breast Density on Background Parenchymal Enhancement in Contrast-Enhanced Mammography and the Need for a Structured Reporting System
ClinicalTrials.gov study NCT06838117. IPD Sharing: NO. Countries: 1. Publications: 0.
Tomosynthesis vs. Contrast-Enhanced Mammography in Women With Personal History of Breast Cancer in Western Pennsylvania
ClinicalTrials.gov study NCT04085510. IPD Sharing: YES. Countries: 1. Publications: 0.
Second-Look Ultrasound Post Contrast-Enhanced Mammography for Additional Lesions Characterization
ClinicalTrials.gov study NCT06846814. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.