AIMC Topic:
Magnetic Resonance Imaging
Clear Filters Showing 1681 to 1690 of 6071 articles
Brain metastasis tumor segmentation and detection using deep learning algorithms: A systematic review and meta-analysis.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Nov 13, 2023
BACKGROUND: Manual detection of brain metastases is both laborious and inconsistent, driving the need for more efficient solutions. Accordingly, our systematic review and meta-analysis assessed the efficacy of deep learning algorithms in detecting an...
Utilizing deep learning via the 3D U-net neural network for the delineation of brain stroke lesions in MRI image.
Scientific reports
Nov 13, 2023
The segmentation of acute stroke lesions plays a vital role in healthcare by assisting doctors in making prompt and well-informed treatment choices. Although Magnetic Resonance Imaging (MRI) is a time-intensive procedure, it produces high-fidelity im...
Simplifying radiologic reports with natural language processing: a novel approach using ChatGPT in enhancing patient understanding of MRI results.
Archives of orthopaedic and trauma surgery
Nov 11, 2023
PURPOSE: The aim of this prospective cohort study was to assess the factual accuracy, completeness of medical information, and potential harmfulness of incorrect conclusions by medical professionals in automatically generated texts of varying complex...
Editorial for "A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI".
Journal of magnetic resonance imaging : JMRI
Nov 10, 2023
Automated Segmentation and Classification of Knee Synovitis Based on MRI Using Deep Learning.
Academic radiology
Nov 10, 2023
OBJECTIVES: To develop a deep learning (DL) model for segmentation of the suprapatellar capsule (SC) and infrapatellar fat pad (IPFP) based on sagittal proton density-weighted images and to distinguish between three common types of knee synovitis.
SIMPLEX: Multiple phase-cycled bSSFP quantitative magnetization transfer imaging with physic-guided simulation learning of neural network.
NeuroImage
Nov 10, 2023
Most quantitative magnetization transfer (qMT) imaging methods require acquiring additional quantitative maps (such as T) for data fitting. A method based on multiple phase-cycled bSSFP was recently proposed to enable high-resolution 3D qMT imaging b...
A narrative review of radiomics and deep learning advances in neuroblastoma: updates and challenges.
Pediatric radiology
Nov 10, 2023
Neuroblastoma is an extremely heterogeneous tumor that commonly occurs in children. The diagnosis and treatment of this tumor pose considerable challenges due to its varied clinical presentations and intricate genetic aberrations. Presently, various ...
MRI-based automatic identification and segmentation of extrahepatic cholangiocarcinoma using deep learning network.
BMC cancer
Nov 10, 2023
BACKGROUND: Accurate identification of extrahepatic cholangiocarcinoma (ECC) from an image is challenging because of the small size and complex background structure. Therefore, considering the limitation of manual delineation, it's necessary to devel...
MRI Deep Learning-Based Automatic Segmentation of Interventricular Septum for Black-Blood Myocardial T2* Measurement in Thalassemia.
Journal of magnetic resonance imaging : JMRI
Nov 9, 2023
BACKGROUND: The T2* value of interventricular septum is routinely reported for grading myocardial iron load in thalassemia major, and automatic segmentation of septum could shorten analysis time and reduce interobserver variability.
Voxel-based morphometry in single subjects without a scanner-specific normal database using a convolutional neural network.
European radiology
Nov 9, 2023
OBJECTIVES: Reliable detection of disease-specific atrophy in individual T1w-MRI by voxel-based morphometry (VBM) requires scanner-specific normal databases (NDB), which often are not available. The aim of this retrospective study was to design, trai...
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