AIMC Topic: Magnetic Resonance Imaging

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Recent Advancements in Fuzzy C-means Based Techniques for Brain MRI Segmentation.

Current medical imaging
BACKGROUND: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques.

Construction of MRI-Based Alzheimer's Disease Score Based on Efficient 3D Convolutional Neural Network: Comprehensive Validation on 7,902 Images from a Multi-Center Dataset.

Journal of Alzheimer's disease : JAD
BACKGROUND: In recent years, many convolutional neural networks (CNN) have been proposed for the classification of Alzheimer's disease. Due to memory constraints, many of the proposed CNNs work at a 2D slice-level or 3D patch-level.

Multi-modal Medical Image Fusion Algorithm Based on Spatial Frequency Motivated PA-PCNN in the NSST Domain.

Current medical imaging
BACKGROUND: Image fusion has been grown as an effectual method in diseases related diagnosis schemes.

Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution.

Cerebral cortex (New York, N.Y. : 1991)
Accurate and automated reconstruction of the in vivo human cerebral cortical surface from anatomical magnetic resonance (MR) images facilitates the quantitative analysis of cortical structure. Anatomical MR images with sub-millimeter isotropic spatia...

Diagnosis of Alzheimer's Disease Based on Deeply-Fused Nets.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: Fast and accurate diagnosis of Alzheimer's disease is very important for the care and further treatment of patients. Along with the development of deep learning, impressive progress has also been made in the automatic diagnosis of ...

Brain Tumor Segmentation of T1w MRI Images Based on Clustering Using Dimensionality Reduction Random Projection Technique.

Current medical imaging
BACKGROUND: Early diagnosis of a brain tumor may increase life expectancy. Magnetic resonance imaging (MRI) accompanied by several segmentation algorithms is preferred as a reliable method for assessment. The availability of high-dimensional medical ...

DeepDicomSort: An Automatic Sorting Algorithm for Brain Magnetic Resonance Imaging Data.

Neuroinformatics
With the increasing size of datasets used in medical imaging research, the need for automated data curation is arising. One important data curation task is the structured organization of a dataset for preserving integrity and ensuring reusability. Th...

An efficient approach to diagnose brain tumors through deep CNN.

Mathematical biosciences and engineering : MBE
BACKGROUND AND OBJECTIVE: Brain tumors are among the most common complications with debilitating or even death potential. Timely detection of brain tumors particularly at an early stage can lead to successful treatment of the patients. In this regard...

[Computed tomography or cardiovascular magnetic resonance imaging for diagnosis of chronic coronary syndrome?].

Der Radiologe
BACKGROUND: Noninvasive imaging modalities are of central importance in the diagnosis of chronic coronary syndrome (CCS) in the current guidelines of the European Society of Cardiology (ESC), while the role of primary invasive coronary angiography in...

Does Artificial Intelligence Outperform Natural Intelligence in Interpreting Musculoskeletal Radiological Studies? A Systematic Review.

Clinical orthopaedics and related research
BACKGROUND: Machine learning (ML) is a subdomain of artificial intelligence that enables computers to abstract patterns from data without explicit programming. A myriad of impactful ML applications already exists in orthopaedics ranging from predicti...