AI Medical Compendium Topic

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Multimodal Imaging

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Multimodal US-gamma imaging using collaborative robotics for cancer staging biopsies.

International journal of computer assisted radiology and surgery
PURPOSE: The staging of female breast cancer requires detailed information about the level of cancer spread through the lymphatic system. Common practice to obtain this information for patients with early-stage cancer is sentinel lymph node (SLN) bio...

Machine Learning Techniques in Clinical Vision Sciences.

Current eye research
This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and tr...

Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI.

IEEE transactions on bio-medical engineering
OBJECTIVE: To obtain high-quality positron emission tomography (PET) image with low-dose tracer injection, this study attempts to predict the standard-dose PET (S-PET) image from both its low-dose PET (L-PET) counterpart and corresponding magnetic re...

Folded concave penalized learning in identifying multimodal MRI marker for Parkinson's disease.

Journal of neuroscience methods
BACKGROUND: Brain MRI holds promise to gauge different aspects of Parkinson's disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data.

Machine learning and dyslexia: Classification of individual structural neuro-imaging scans of students with and without dyslexia.

NeuroImage. Clinical
Meta-analytic studies suggest that dyslexia is characterized by subtle and spatially distributed variations in brain anatomy, although many variations failed to be significant after corrections of multiple comparisons. To circumvent issues of signifi...

Multimodal hybrid imaging agents for sentinel node mapping as a means to (re)connect nuclear medicine to advances made in robot-assisted surgery.

European journal of nuclear medicine and molecular imaging
PURPOSE: Radical prostatectomy and complementary extended pelvic lymph node dissection (ePLND) of sentinel lymph nodes (SNs) and non-sentinel lymph nodes (LNs) at risk of containing metastases are increasingly being performed using high-tech robot-as...

Combined unsupervised-supervised classification of multiparametric PET/MRI data: application to prostate cancer.

NMR in biomedicine
Multiparametric medical imaging data can be large and are often complex. Machine learning algorithms can assist in image interpretation when reliable training data exist. In most cases, however, knowledge about ground truth (e.g. histology) and thus ...

Multimodal analysis of functional and structural disconnection in Alzheimer's disease using multiple kernel SVM.

Human brain mapping
Alzheimer's disease (AD) patients exhibit alterations in the functional connectivity between spatially segregated brain regions which may be related to both local gray matter (GM) atrophy as well as a decline in the fiber integrity of the underlying ...

Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND: Alzheimer's disease (AD) patients show early changes in white matter (WM) structural integrity. We studied the use of diffusion tensor imaging (DTI) in assessing WM alterations in the predementia stage of mild cognitive impairment (MCI).

Manifold regularized multitask feature learning for multimodality disease classification.

Human brain mapping
Multimodality based methods have shown great advantages in classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint select...