AIMC Topic: Magnetic Resonance Imaging
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Federated learning with integrated attention multiscale model for brain tumor segmentation.
Scientific reports
Apr 7, 2025
Brain tumors are an extremely deadly condition and the growth of abnormal cells that have formed inside the brain causes the illness. According to studies, Magnetic Resonance Imaging (MRI) is a fundamental imaging method that is frequently used in me...
Ensemble deep learning for Alzheimer's disease diagnosis using MRI: Integrating features from VGG16, MobileNet, and InceptionResNetV2 models.
PloS one
Apr 7, 2025
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain, leading to distinctive patterns of neuronal dysfunction and the cognitive decline emblematic of de...
Structural brain pattern abnormalities in tinnitus with and without hearing loss.
Hearing research
Apr 6, 2025
OBJECTIVE: Subjective tinnitus often coexists with hearing loss, and they share common pathophysiological mechanisms. This comorbidity induces whole-brain gray matter volume (GMV) alterations, manifesting as distributed structural changes in neural n...
Complex-valued neural networks to speed-up MR thermometry during hyperthermia using Fourier PD and PDUNet.
Scientific reports
Apr 6, 2025
Hyperthermia (HT) in combination with radio- and/or chemotherapy has become an accepted cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously heated to temperatures between 39 and 43 °C for 60 min. Temperature monit...
Longitudinal study on the impact of short-term radiological interpretation training on resting-state brain network hubs.
Trends in neuroscience and education
Apr 5, 2025
Radiological expertise develops through extensive experience in specific imaging modalities. While previous research has focused on long-term learning and neural mechanisms of expertise, the effects of short-term radiological training on resting-stat...
Unsupervised brain MRI tumour segmentation via two-stage image synthesis.
Medical image analysis
Apr 5, 2025
Deep learning shows promise in automated brain tumour segmentation, but it depends on costly expert annotations. Recent advances in unsupervised learning offer an alternative by using synthetic data for training. However, the discrepancy between real...
The impact of Alzheimer's disease on cortical complexity and its underlying biological mechanisms.
Brain research bulletin
Apr 4, 2025
BACKGROUND: Alzheimer's disease (AD) might impact the complexity of cerebral cortex, and the underlying biological mechanisms responsible for cortical changes in the AD cortex remain unclear.
Deep-learning synthetized 4DCT from 4DMRI of the abdominal site in carbon-ion radiotherapy.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 4, 2025
PURPOSE: To investigate the feasibility of deep-learning-based synthetic 4DCT (4D-sCT) generation from 4DMRI data of abdominal patients undergoing Carbon Ion Radiotherapy (CIRT).
A fine-tuned convolutional neural network model for accurate Alzheimer's disease classification.
Scientific reports
Apr 4, 2025
Alzheimer's disease (AD) is one of the primary causes of dementia in the older population, affecting memories, cognitive levels, and the ability to accomplish simple activities gradually. Timely intervention and efficient control of the disease prove...
A semantic segmentation model for automatic precise identification of pituitary microadenomas with preoperative MRI.
Neuroradiology
Apr 4, 2025
PURPOSE: Magnetic resonance imaging (MRI) is an essential technique for diagnosing pituitary adenomas; however, it is also challenging for neurosurgeons to use it to precisely identify some types of microadenomas. A novel neural network model was dev...
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