AIMC Topic: Magnetic Resonance Imaging

Clear Filters Showing 3091 to 3100 of 6192 articles

Preliminary study of generalized semiautomatic segmentation for 3D voxel labeling of lesions based on deep learning.

International journal of computer assisted radiology and surgery Oct 15, 2021
PURPOSE: The three-dimensional (3D) voxel labeling of lesions requires significant radiologists' effort in the development of computer-aided detection software. To reduce the time required for the 3D voxel labeling, we aimed to develop a generalized ...
Magnetic Resonance Imaging Liver Humans Thorax Tomography, X-Ray Computed Deep Learning
View on PubMed DOI

Structure can predict function in the human brain: a graph neural network deep learning model of functional connectivity and centrality based on structural connectivity.

Brain structure & function Oct 11, 2021
Although functional connectivity and associated graph theory measures (e.g., centrality; how centrally important to the network a region is) are widely used in brain research, the full extent to which these functional measures are related to the unde...
Humans Brain Connectome Deep Learning Neural Pathways Magnetic Resonance Imaging Nerve Net
View on PubMed DOI

CST: A Multitask Learning Framework for Colorectal Cancer Region Mining Based on Transformer.

BioMed research international Oct 11, 2021
Colorectal cancer is a high death rate cancer until now; from the clinical view, the diagnosis of the tumour region is critical for the doctors. But with data accumulation, this task takes lots of time and labor with large variances between different...
Magnetic Resonance Imaging Early Detection of Cancer Algorithms Colorectal Neoplasms Humans Image Processing, Computer-Assisted Artificial Intelligence
View on PubMed DOI

Subject-Specific Cognitive Workload Classification Using EEG-Based Functional Connectivity and Deep Learning.

Sensors (Basel, Switzerland) Oct 9, 2021
Cognitive workload is a crucial factor in tasks involving dynamic decision-making and other real-time and high-risk situations. Neuroimaging techniques have long been used for estimating cognitive workload. Given the portability, cost-effectiveness a...
Neural Networks, Computer Magnetic Resonance Imaging Deep Learning Electroencephalography Cognition Humans
View on PubMed DOI

Deep learning-based classification and structure name standardization for organ at risk and target delineations in prostate cancer radiotherapy.

Journal of applied clinical medical physics Oct 8, 2021
Radiotherapy (RT) datasets can suffer from variations in annotation of organ at risk (OAR) and target structures. Annotation standards exist, but their description for prostate targets is limited. This restricts the use of such data for supervised ma...
Humans Male Prostatic Neoplasms Deep Learning Magnetic Resonance Imaging Radiotherapy Planning, Computer-Assisted Reference Standards
View on PubMed DOI

Predicting cognitive impairment in outpatients with epilepsy using machine learning techniques.

Scientific reports Oct 8, 2021
Many studies report predictions for cognitive function but there are few predictions in epileptic patients; therefore, we established a workflow to efficiently predict outcomes of both the Mini-Mental State Examination (MMSE) and Montreal Cognitive A...
Magnetic Resonance Imaging Epilepsy Outpatients Neuropsychological Tests Seizures Male Cognitive Dysfunction Treatment Outcome Machine Learning Risk Factors Biomarkers Humans Adult Prognosis Female Brain
View on PubMed DOI

Annotation-efficient deep learning for automatic medical image segmentation.

Nature communications Oct 8, 2021
Automatic medical image segmentation plays a critical role in scientific research and medical care. Existing high-performance deep learning methods typically rely on large training datasets with high-quality manual annotations, which are difficult to...
Female Breast Neoplasms Deep Learning Humans Retrospective Studies Datasets as Topic Image Processing, Computer-Assisted Magnetic Resonance Imaging
View on PubMed DOI

SMBFT: A Modified Fuzzy -Means Algorithm for Superpixel Generation.

Computational and mathematical methods in medicine Oct 8, 2021
Most traditional superpixel segmentation methods used binary logic to generate superpixels for natural images. When these methods are used for images with significantly fuzzy characteristics, the boundary pixels sometimes cannot be correctly classifi...
Magnetic Resonance Imaging Image Processing, Computer-Assisted Fuzzy Logic Algorithms Computational Biology Humans Pattern Recognition, Automated Image Interpretation, Computer-Assisted Brain
View on PubMed DOI

Recovering SWI-filtered phase data using deep learning.

Magnetic resonance in medicine Oct 5, 2021
PURPOSE: To develop a deep neural network to recover filtered phase from clinical MR phase images to enable the computation of QSMs.
Neural Networks, Computer Brain Image Processing, Computer-Assisted Magnetic Resonance Imaging Deep Learning
View on PubMed DOI

Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial.

Radiology Oct 5, 2021
Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and physiologic variation that may not require radiologic review. Thus, ways to triage these normal MRI...
Breast Neoplasms Middle Aged Deep Learning Humans Female Feasibility Studies Image Interpretation, Computer-Assisted Breast Density Triage Breast Magnetic Resonance Imaging
View on PubMed DOI
Popular Topics
Recent Journals