AIMC Topic: Magnetic Resonance Imaging
Clear Filters Showing 3211 to 3220 of 6200 articles
A Novel Type-2 Fuzzy C-Means Clustering for Brain MR Image Segmentation.
IEEE transactions on cybernetics
Aug 4, 2021
The fuzzy C -means (FCM) clustering procedure is an unsupervised form of grouping the homogenous pixels of an image in the feature space into clusters. A brain magnetic resonance (MR) image is affected by noise and intensity inhomogeneity (IIH) durin...
CAFT: a deep learning-based comprehensive abdominal fat analysis tool for large cohort studies.
Magma (New York, N.Y.)
Aug 2, 2021
BACKGROUND: There is increasing appreciation of the association of obesity beyond co-morbidities, such as cancers, Type 2 diabetes, hypertension, and stroke to also impact upon the muscle to give rise to sarcopenic obesity. Phenotypic knowledge of ob...
Scale- and Slice-aware Net (S aNet) for 3D segmentation of organs and musculoskeletal structures in pelvic MRI.
Magnetic resonance in medicine
Aug 2, 2021
PURPOSE: MRI of organs and musculoskeletal structures in the female pelvis presents a unique display of pelvic anatomy. Automated segmentation of pelvic structures plays an important role in personalized diagnosis and treatment on pelvic structures d...
Simultaneous brain structure segmentation in magnetic resonance images using deep convolutional neural networks.
Radiological physics and technology
Aug 2, 2021
In brain magnetic resonance imaging (MRI) examinations, rapidly acquired two-dimensional (2D) T1-weighted sagittal slices are typically used to confirm brainstem atrophy and the presence of signals in the posterior pituitary gland. Image segmentation...
[Importance of conventional pancreas imaging: ultrasound, CT, and MRI. Facts and possibilities].
Magyar onkologia
Aug 2, 2021
Modern imaging procedures, including CT and MR diagnostics, play a significant role in recognizing, characterizing, determining the extent of pancreatic tumor lesions, assessing their operability, and evaluating response to treatment and patient foll...
Domain knowledge augmentation of parallel MR image reconstruction using deep learning.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 2, 2021
A deep learning (DL) method for accelerated magnetic resonance (MR) imaging is presented that incorporates domain knowledge of parallel MR imaging to augment the DL networks for accurate and stable image reconstruction. The proposed DL method employs...
A deep learning approach for magnetic resonance fingerprinting: Scaling capabilities and good training practices investigated by simulations.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Aug 2, 2021
MR fingerprinting (MRF) is an innovative approach to quantitative MRI. A typical disadvantage of dictionary-based MRF is the explosive growth of the dictionary as a function of the number of reconstructed parameters, an instance of the curse of dimen...
A pipeline to quantify spinal cord atrophy with deep learning: Application to differentiation of MS and NMOSD patients.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Aug 2, 2021
PURPOSE: Quantitative measurement of various anatomical regions of the brain and spinal cord (SC) in MRI images are used as unique biomarkers to consider progress and effects of demyelinating diseases of the central nervous system. This paper present...
Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review.
Computers in biology and medicine
Jul 31, 2021
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor problems for people with a detrimental effect on the functioning of the nervous system. In order to diagnose MS, multiple screening methods have been proposed ...
Deep Learning-Based ECG-Free Cardiac Navigation for Multi-Dimensional and Motion-Resolved Continuous Magnetic Resonance Imaging.
IEEE transactions on medical imaging
Jul 30, 2021
For the clinical assessment of cardiac vitality, time-continuous tomographic imaging of the heart is used. To further detect e.g., pathological tissue, multiple imaging contrasts enable a thorough diagnosis using magnetic resonance imaging (MRI). For...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31144
- Neural Networks, Computer 29771
- Algorithms 26915
- Deep Learning 26421
- Artificial Intelligence 24361
- Robotics 13323
- Image Processing, Computer-Assisted 9552
- Retrospective Studies 9137
- Magnetic Resonance Imaging 6200
- Reproducibility of Results 5602
- Tomography, X-Ray Computed 4778
- Support Vector Machine 4696
- Computational Biology 4246
- Brain 4056
- Computer Simulation 3887
Recent Journals
- Scientific reports 6082
- Sensors (Basel, Switzerland) 4794
- PloS one 4051
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1868
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1137
- Journal of chemical information and modeling 1006
- Nature communications 959
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 862
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 830