AIMC Topic:
Magnetic Resonance Imaging
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Prospective Deployment of Deep Learning Reconstruction Facilitates Highly Accelerated Upper Abdominal MRI.
Academic radiology
Jul 2, 2024
RATIONALE AND OBJECTIVES: To compare a conventional T1 volumetric interpolated breath-hold examination (VIBE) with SPectral Attenuated Inversion Recovery (SPAIR) fat saturation and a deep learning (DL)-reconstructed accelerated VIBE sequence with SPA...
A causal counterfactual graph neural network for arising-from-chair abnormality detection in parkinsonians.
Medical image analysis
Jul 2, 2024
The arising-from-chair task assessment is a key aspect of the evaluation of movement disorders in Parkinson's disease (PD). However, common scale-based clinical assessment methods are highly subjective and dependent on the neurologist's expertise. Al...
A systematic literature review on the significance of deep learning and machine learning in predicting Alzheimer's disease.
Artificial intelligence in medicine
Jul 2, 2024
BACKGROUND: Alzheimer's disease (AD) is the most prevalent cause of dementia, characterized by a steady decline in mental, behavioral, and social abilities and impairs a person's capacity for independent functioning. It is a fatal neurodegenerative d...
Advances in Computational Biology for Diagnosing Neurodegenerative Diseases: A Comprehensive Review.
Zhongguo ying yong sheng li xue za zhi = Zhongguo yingyong shenglixue zazhi = Chinese journal of applied physiology
Jul 2, 2024
The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to contemporary healthcare. The emergence of artificial intelligence has fundamentally changed the diagnostic picture by providing effective and early means...
Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI.
NeuroImage. Clinical
Jul 2, 2024
Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very high dimensionality of neuroimaging data, the relatively small size of...
SymTC: A symbiotic Transformer-CNN net for instance segmentation of lumbar spine MRI.
Computers in biology and medicine
Jul 1, 2024
Intervertebral disc disease, a prevalent ailment, frequently leads to intermittent or persistent low back pain, and diagnosing and assessing of this disease rely on accurate measurement of vertebral bone and intervertebral disc geometries from lumbar...
Classification of brain tumor types through MRIs using parallel CNNs and firefly optimization.
Scientific reports
Jul 1, 2024
Image segmentation is a critical and challenging endeavor in the field of medicine. A magnetic resonance imaging (MRI) scan is a helpful method for locating any abnormal brain tissue these days. It is a difficult undertaking for radiologists to diagn...
7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery.
European radiology experimental
Jul 1, 2024
Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in ar...
Mixed Supervision of Histopathology Improves Prostate Cancer Classification From MRI.
IEEE transactions on medical imaging
Jul 1, 2024
Non-invasive prostate cancer classification from MRI has the potential to revolutionize patient care by providing early detection of clinically significant disease, but has thus far shown limited positive predictive value. To address this, we present...
Shape-Scale Co-Awareness Network for 3D Brain Tumor Segmentation.
IEEE transactions on medical imaging
Jul 1, 2024
The accurate segmentation of brain tumor is significant in clinical practice. Convolutional Neural Network (CNN)-based methods have made great progress in brain tumor segmentation due to powerful local modeling ability. However, brain tumors are freq...
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