AIMC Topic:
Image Interpretation, Computer-Assisted

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Multi-Atlas Segmentation of Anatomical Brain Structures Using Hierarchical Hypergraph Learning.

IEEE transactions on neural networks and learning systems Sep 5, 2019
Accurate segmentation of anatomical brain structures is crucial for many neuroimaging applications, e.g., early brain development studies and the study of imaging biomarkers of neurodegenerative diseases. Although multi-atlas segmentation (MAS) has a...
Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Deep Learning Brain Mapping Databases, Factual Brain
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Deep Learning Based Noise Reduction for Brain MR Imaging: Tests on Phantoms and Healthy Volunteers.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Sep 4, 2019
PURPOSE: To test whether our proposed denoising approach with deep learning-based reconstruction (dDLR) can effectively denoise brain MR images.
Magnetic Resonance Imaging Humans Image Interpretation, Computer-Assisted Brain Phantoms, Imaging Deep Learning Signal-To-Noise Ratio
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Long-term follow-up of persistent pulmonary pure ground-glass nodules with deep learning-assisted nodule segmentation.

European radiology Sep 4, 2019
OBJECTIVE: To investigate the natural history of persistent pulmonary pure ground-glass nodules (pGGNs) with deep learning-assisted nodule segmentation.
Retrospective Studies Tomography, X-Ray Computed Female Risk Factors Humans Algorithms Deep Learning Lung Neoplasms Follow-Up Studies Solitary Pulmonary Nodule Male Middle Aged Lung Regression Analysis Image Interpretation, Computer-Assisted Time
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Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.

The Journal of pathology Sep 3, 2019
In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated pa...
Humans Artificial Intelligence Diagnosis, Computer-Assisted Predictive Value of Tests Terminology as Topic Pathology Workflow Computer Security Benchmarking Policy Making Image Interpretation, Computer-Assisted
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Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis.

IEEE transactions on cybernetics Sep 2, 2019
Histopathology image analysis serves as the gold standard for cancer diagnosis. Efficient and precise diagnosis is quite critical for the subsequent therapeutic treatment of patients. So far, computer-aided diagnosis has not been widely applied in pa...
Supervised Machine Learning Image Interpretation, Computer-Assisted Histocytochemistry Deep Learning Humans Lung Neoplasms
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Image-based Classification of Tumor Type and Growth Rate using Machine Learning: a preclinical study.

Scientific reports Aug 29, 2019
Medical images such as magnetic resonance (MR) imaging provide valuable information for cancer detection, diagnosis, and prognosis. In addition to the anatomical information these images provide, machine learning can identify texture features from th...
Image Interpretation, Computer-Assisted Glioma Magnetic Resonance Imaging Neoplasm Staging Neural Networks, Computer Humans Machine Learning Algorithms Brain Neoplasms
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Development of accurate human head models for personalized electromagnetic dosimetry using deep learning.

NeuroImage Aug 28, 2019
The development of personalized human head models from medical images has become an important topic in the electromagnetic dosimetry field, including the optimization of electrostimulation, safety assessments, etc. Human head models are commonly gene...
Models, Biological Adult Image Interpretation, Computer-Assisted Electromagnetic Fields Middle Aged Head Transcranial Magnetic Stimulation Humans Deep Learning Male Brain Magnetic Resonance Imaging
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Connectomic Profiling Identifies Responders to Vagus Nerve Stimulation.

Annals of neurology Aug 27, 2019
OBJECTIVE: Vagus nerve stimulation (VNS) is a common treatment for medically intractable epilepsy, but response rates are highly variable, with no preoperative means of identifying good candidates. This study aimed to predict VNS response using struc...
Female Vagus Nerve Stimulation Male Diffusion Tensor Imaging Adolescent Drug Resistant Epilepsy Treatment Outcome Magnetoencephalography Support Vector Machine Patient Selection Child, Preschool Image Interpretation, Computer-Assisted Child Humans Connectome
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Predicting PET-derived demyelination from multimodal MRI using sketcher-refiner adversarial training for multiple sclerosis.

Medical image analysis Aug 24, 2019
Multiple sclerosis (MS) is the most common demyelinating disease. In MS, demyelination occurs in the white matter of the brain and in the spinal cord. It is thus essential to measure the tissue myelin content to understand the physiopathology of MS, ...
Multiple Sclerosis Humans Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Neural Networks, Computer Anisotropy Radiopharmaceuticals Disease Progression Positron-Emission Tomography
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Identifying schizophrenia subgroups using clustering and supervised learning.

Schizophrenia research Aug 24, 2019
Schizophrenia has a 1% incidence rate world-wide and those diagnosed present with positive (e.g. hallucinations, delusions), negative (e.g. apathy, asociality), and cognitive symptoms. However, both symptom burden and associated brain alterations are...
Female Humans Adult Brain Schizophrenia Male Organ Size Image Interpretation, Computer-Assisted Severity of Illness Index Pattern Recognition, Automated Area Under Curve Psychiatric Status Rating Scales Supervised Machine Learning Magnetic Resonance Imaging Cluster Analysis
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