AIMC Topic:
Magnetic Resonance Imaging

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Imaging segmentation mechanism for rectal tumors using improved U-Net.

BMC medical imaging Apr 23, 2024
OBJECTIVE: In radiation therapy, cancerous region segmentation in magnetic resonance images (MRI) is a critical step. For rectal cancer, the automatic segmentation of rectal tumors from an MRI is a great challenge. There are two main shortcomings in ...
Rectal Neoplasms Image Interpretation, Computer-Assisted Male Humans Deep Learning Magnetic Resonance Imaging Neural Networks, Computer
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An Intuitionistic Fuzzy C-Means and Local Information-Based DCT Filtering for Fast Brain MRI Segmentation.

Journal of imaging informatics in medicine Apr 22, 2024
Structural and photometric anomalies in the brain magnetic resonance images (MRIs) affect the segmentation performance. Moreover, a sudden change in intensity between two boundaries of the brain tissues makes it prone to data uncertainty, resulting i...
Humans Algorithms Fuzzy Logic Cluster Analysis Brain Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Effect of MR head coil geometry on deep-learning-based MR image reconstruction.

Magnetic resonance in medicine Apr 22, 2024
PURPOSE: To investigate whether parallel imaging-imposed geometric coil constraints can be relaxed when using a deep learning (DL)-based image reconstruction method as opposed to a traditional non-DL method.
Signal-To-Noise Ratio Deep Learning Humans Phantoms, Imaging Image Processing, Computer-Assisted Algorithms Magnetic Resonance Imaging Brain Head
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DF-QSM: Data Fidelity based Hybrid Approach for Improved Quantitative Susceptibility Mapping of the Brain.

NMR in biomedicine Apr 22, 2024
Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique to quantify the magnetic susceptibility of the tissue under investigation. Deep learning methods have shown promising results in deconvolving the susc...
Brain Mapping Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Algorithms Adult Male Brain Female
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Diagnostic support in pediatric craniopharyngioma using deep learning.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery Apr 22, 2024
PURPOSE: We studied a pediatric group of patients with sellar-suprasellar tumors, aiming to develop a convolutional deep learning algorithm for radiological assistance to classify them into their respective cohort.
Humans Female Male Child Magnetic Resonance Imaging Pituitary Neoplasms Craniopharyngioma Deep Learning Adolescent Child, Preschool
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Advancing musculoskeletal tumor diagnosis: Automated segmentation and predictive classification using deep learning and radiomics.

Computers in biology and medicine Apr 22, 2024
OBJECTIVES: Musculoskeletal (MSK) tumors, given their high mortality rate and heterogeneity, necessitate precise examination and diagnosis to guide clinical treatment effectively. Magnetic resonance imaging (MRI) is pivotal in detecting MSK tumors, a...
Humans Adult Image Interpretation, Computer-Assisted Muscle Neoplasms Radiomics Algorithms Deep Learning Male Female Magnetic Resonance Imaging Middle Aged Bone Neoplasms Aged
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External evaluation of a deep learning-based approach for automated brain volumetry in patients with huntington's disease.

Scientific reports Apr 22, 2024
A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for au...
Caudate Nucleus Organ Size Atrophy Huntington Disease Deep Learning Brain Image Processing, Computer-Assisted Humans Retrospective Studies Magnetic Resonance Imaging Software Female Male Aged Middle Aged Adult
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Deep learning for discrimination of active and inactive lesions in multiple sclerosis using non-contrast FLAIR MRI: A multicenter study.

Multiple sclerosis and related disorders Apr 21, 2024
BACKGROUND: Within the domain of multiple sclerosis (MS), the precise discrimination between active and inactive lesions bears immense significance. Active lesions are enhanced on T1-weighted MRI images after administration of gadolinium-based contra...
Male Middle Aged Female Deep Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Humans Adult Sensitivity and Specificity Multiple Sclerosis Neural Networks, Computer Brain
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MRI super-resolution using similarity distance and multi-scale receptive field based feature fusion GAN and pre-trained slice interpolation network.

Magnetic resonance imaging Apr 21, 2024
Challenges arise in achieving high-resolution Magnetic Resonance Imaging (MRI) to improve disease diagnosis accuracy due to limitations in hardware, patient discomfort, long acquisition times, and high costs. While Convolutional Neural Networks (CNNs...
Algorithms Brain Humans Imaging, Three-Dimensional Image Processing, Computer-Assisted Neural Networks, Computer Magnetic Resonance Imaging
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Deep learning-based arterial subtraction images improve the detection of LR-TR algorithm for viable HCC on extracellular agents-enhanced MRI.

Abdominal radiology (New York) Apr 20, 2024
PURPOSE: To determine the role of deep learning-based arterial subtraction images in viability assessment on extracellular agents-enhanced MRI using LR-TR algorithm.
Male Middle Aged Deep Learning Image Interpretation, Computer-Assisted Liver Neoplasms Carcinoma, Hepatocellular Image Enhancement Angiography, Digital Subtraction Humans Female Aged, 80 and over Contrast Media Algorithms Subtraction Technique Aged Adult Magnetic Resonance Imaging Retrospective Studies Sensitivity and Specificity
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