AIMC Topic: Magnetic Resonance Imaging

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Modality-projection universal model for comprehensive full-body medical imaging segmentation.

Nature communications
The integration of deep learning in medical imaging has significantly advanced diagnostic, therapeutic, and research outcomes. However, applying universal models across multiple modalities remains challenging due to inherent inter-modality variabilit...

Evaluation of radiosensitivity for high grade gliomas patients using a multi-temporal graph convolutional networks.

Physics in medicine and biology
Assessing the efficacy of radiotherapy in patients with high-grade gliomas (HGGs) is challenging due to the occurrence of pseudo-progression and radionecrosis. This study introduces a directed graph network leveraging MR image features at multiple ti...

IV3TM: Inception V3 enabled bidirectional long short-term memory network for brain tumor classification.

PloS one
A brain tumor is one of the life-threatening neurological conditions affecting millions of people worldwide. Early diagnosis and classification of brain tumor types facilitate prompt treatment, thereby increasing the patient's chances of survival. Th...

Application of multimodal integration to develop preoperative diagnostic models for borderline and malignant ovarian tumors.

Scientific reports
Malignant ovarian tumors (MOTs) and borderline ovarian tumors (BOTs) differ in treatment strategies and prognosis. However, accurate preoperative diagnosis remains challenging, and improving diagnostic accuracy is crucial. We developed and validated ...

Categorical and phenotypic image synthetic learning as an alternative to federated learning.

Nature communications
Multi-center collaborations are crucial in developing robust and generalizable machine learning models in medical imaging. Traditional methods, such as centralized data sharing or federated learning (FL), face challenges, including privacy issues, co...

Heterogeneity of human insular cortex: five principles of functional organization across multiple cognitive domains.

Brain structure & function
The insular cortex serves as a critical hub for human cognition, but how its anatomically distinct subregions coordinate diverse cognitive, emotional, and social functions remains unclear. Using the Human Connectome Project's multi-task fMRI dataset ...

Deep learning-driven contactless ECG in MRI via beat pilot tone for motion-resolved image reconstruction and heart rate monitoring.

Physics in medicine and biology
Electrocardiogram (ECG) is crucial for synchronizing cardiovascular magnetic resonance imaging (CMRI) acquisition with the cardiac cycle and for continuous heart rate monitoring during prolonged scans. However, conventional electrode-based ECG system...

Multimodal integration of plasma biomarkers, MRI, and genetic risk to predict cerebral amyloid burden in Alzheimer's disease.

NeuroImage
Alzheimer's disease (AD), the most prevalent neurodegenerative disorder, is marked by the accumulation of amyloid-β (Aβ) plaques. Although cerebral Aβ positron emission tomography (Aβ-PET) remains the gold standard for assessing cerebral Aβ burden, i...

Functional motor mapping of domestic pig lumbar spinal cord using penetrating microelectrodes.

Journal of neuroengineering and rehabilitation
The restoration of standing and walking after spinal cord injury (SCI) remains a top priority for individuals with paraplegia. Despite significant advancements in neuromodulation techniques, challenges such as limited selectivity and inconsistent out...

Deep multi-instance learning model based on gadoxetic acid-enhanced MRI for predicting microvascular invasion of hepatocellular carcinoma: a multicenter, retrospective study.

BMC cancer
OBJECTIVE: Microvascular invasion (MVI) is of great significance for the individualized treatment of hepatocellular carcinoma (HCC) and preoperative noninvasive prediction of MVI is still an urgent clinical problem. To explore the effects of differen...