AIMC Topic: Magnetic Resonance Imaging
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography.
NeuroImage
Jan 23, 2025
Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are pr...
Enhanced detection of mild cognitive impairment in Alzheimer's disease: a hybrid model integrating dual biomarkers and advanced machine learning.
BMC geriatrics
Jan 23, 2025
Alzheimer's disease (AD) is a complex, progressive, and irreversible neurodegenerative disorder marked by cognitive decline and memory loss. Early diagnosis is the most effective strategy to slow the disease's progression. Mild Cognitive Impairment (...
Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning.
Abdominal radiology (New York)
Jan 22, 2025
PURPOSE: Intra-pancreatic fat deposition (IPFD) is closely associated with the onset and progression of type 2 diabetes mellitus (T2DM). We aimed to develop an accurate and automated method for assessing IPFD on multi-echo Dixon MRI.
Multi-parametric MRI combined with radiomics for the diagnosis and grading of endometrial fibrosis.
Abdominal radiology (New York)
Jan 22, 2025
PURPOSE: To evaluate the application of multi-parametric MRI (MP-MRI) combined with radiomics in diagnosing and grading endometrial fibrosis (EF).
Automated vs manual cardiac MRI planning: a single-center prospective evaluation of reliability and scan times.
European radiology
Jan 22, 2025
OBJECTIVES: Evaluating the impact of an AI-based automated cardiac MRI (CMR) planning software on procedure errors and scan times compared to manual planning alone.
MR-linac: role of artificial intelligence and automation.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Jan 22, 2025
The integration of artificial intelligence (AI) into radiotherapy has advanced significantly during the past 5 years, especially in terms of automating key processes like organ at risk delineation and treatment planning. These innovations have enhanc...
A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity.
Scientific reports
Jan 22, 2025
Functional connectivity holds promise as a biomarker of schizophrenia. Yet, the high dimensionality of predictive models trained on functional connectomes, combined with small sample sizes in clinical research, increases the risk of overfitting. Rece...
CDCG-UNet: Chaotic Optimization Assisted Brain Tumor Segmentation Based on Dilated Channel Gate Attention U-Net Model.
Neuroinformatics
Jan 22, 2025
Brain tumours are one of the most deadly and noticeable types of cancer, affecting both children and adults. One of the major drawbacks in brain tumour identification is the late diagnosis and high cost of brain tumour-detecting devices. Most existin...
Multimodal multiview bilinear graph convolutional network for mild cognitive impairment diagnosis.
Biomedical physics & engineering express
Jan 22, 2025
Mild cognitive impairment (MCI) is a significant predictor of the early progression of Alzheimer's disease (AD) and can serve as an important indicator of disease progression. However, many existing methods focus mainly on the image when processing b...
Contrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions.
Journal of hepatology
Jan 21, 2025
BACKGROUND & AIMS: Accurate multi-classification is a prerequisite for appropriate management of focal liver lesions (FLLs). Ultrasound is the most common imaging examination but lacks accuracy. Contrast-enhanced ultrasound (CEUS) offers better perfo...
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