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Positron-Emission Tomography

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Neural correlates of consciousness in patients who have emerged from a minimally conscious state: a cross-sectional multimodal imaging study.

The Lancet. Neurology
BACKGROUND: Between pathologically impaired consciousness and normal consciousness exists a scarcely researched transition zone, referred to as emergence from minimally conscious state, in which patients regain the capacity for functional communicati...

Ensembles of Deep Learning Architectures for the Early Diagnosis of the Alzheimer's Disease.

International journal of neural systems
Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be simpler and more likely to be effective. This paper explores the constr...

Clinical and oncologic outcomes of totally robotic total mesorectal excision for rectal cancer: initial results in a center for minimally invasive surgery.

International journal of colorectal disease
PURPOSE: A robotic system was mainly designed to allow precise dissection in deep and narrow spaces. We report the clinical and oncologic outcomes of totally robotic total mesorectal excision for rectal cancer.

Monitoring vascular normalization induced by antiangiogenic treatment with (18)F-fluoromisonidazole-PET.

Molecular oncology
BACKGROUND: Rationalization of antiangiogenics requires biomarkers. Vascular re-normalization is one widely accepted mechanism of action for this drug class. The interstitium of tumors with abnormal vasculature is hypoxic. We sought to track vascular...

Graph-guided joint prediction of class label and clinical scores for the Alzheimer's disease.

Brain structure & function
Accurate diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, is very important for early treatment. Over the last decade, various machine learning methods have been proposed to predict disease status and clinica...

Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks.

PloS one
Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has become a standard component of diagnosis and staging in oncology, and is becoming more important as a quantitative monitor of individual response to therapy....

Enhancing spatial resolution of (18)F positron imaging with the Timepix detector by classification of primary fired pixels using support vector machine.

Physics in medicine and biology
Position-sensitive positron cameras using silicon pixel detectors have been applied for some preclinical and intraoperative clinical applications. However, the spatial resolution of a positron camera is limited by positron multiple scattering in the ...

Transoral robotic surgery for the management of head and neck squamous cell carcinoma of unknown primary.

Acta oto-laryngologica
CONCLUSION: The addition of transoral robotic surgery (TORS) in the diagnostic management of patients classified with head and neck squamous cell carcinoma of unknown primary (SCCUP) is promising and appears to improve detection rates of the primary ...

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 ...

Deep sparse multi-task learning for feature selection in Alzheimer's disease diagnosis.

Brain structure & function
Recently, neuroimaging-based Alzheimer's disease (AD) or mild cognitive impairment (MCI) diagnosis has attracted researchers in the field, due to the increasing prevalence of the diseases. Unfortunately, the unfavorable high-dimensional nature of neu...