AIMC Topic: Image Processing, Computer-Assisted

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Development of the brain's structural network efficiency in early adolescence: A longitudinal DTI twin study.

Human brain mapping
The brain is a network and our intelligence depends in part on the efficiency of this network. The network of adolescents differs from that of adults suggesting developmental changes. However, whether the network changes over time at the individual l...

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....

Temporal stability of network centrality in control and default mode networks: Specific associations with externalizing psychopathology in children and adolescents.

Human brain mapping
Abnormal connectivity patterns have frequently been reported as involved in pathological mental states. However, most studies focus on "static," stationary patterns of connectivity, which may miss crucial biological information. Recent methodological...

Machine learning classification of mesial temporal sclerosis in epilepsy patients.

Epilepsy research
BACKGROUND AND PURPOSE: Novel approaches applying machine-learning methods to neuroimaging data seek to develop individualized measures that will aid in the diagnosis and treatment of brain-based disorders such as temporal lobe epilepsy (TLE). Using ...

Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.

Proceedings of the National Academy of Sciences of the United States of America
A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new in...

Going beyond a First Reader: A Machine Learning Methodology for Optimizing Cost and Performance in Breast Ultrasound Diagnosis.

Ultrasound in medicine & biology
The goal of this study was to devise a machine learning methodology as a viable low-cost alternative to a second reader to help augment physicians' interpretations of breast ultrasound images in differentiating benign and malignant masses. Two indepe...

An Inversion Scheme for Hybrid Fluorescence Molecular Tomography Using a Fuzzy Inference System.

IEEE transactions on medical imaging
The imaging performance of fluorescence molecular tomography (FMT) improves when information from the underlying anatomy is incorporated into the inversion scheme, in the form of priors. The requirement for incorporation of priors has recently driven...

Dictionary-Driven Ischemia Detection From Cardiac Phase-Resolved Myocardial BOLD MRI at Rest.

IEEE transactions on medical imaging
Cardiac Phase-resolved Blood-Oxygen-Level Dependent (CP-BOLD) MRI provides a unique opportunity to image an ongoing ischemia at rest. However, it requires post-processing to evaluate the extent of ischemia. To address this, here we propose an unsuper...

Influence of Errors in Tactile Sensors on Some High Level Parameters Used for Manipulation with Robotic Hands.

Sensors (Basel, Switzerland)
Tactile sensors suffer from many types of interference and errors like crosstalk, non-linearity, drift or hysteresis, therefore calibration should be carried out to compensate for these deviations. However, this procedure is difficult in sensors moun...

Assessing hippocampal development and language in early childhood: Evidence from a new application of the Automatic Segmentation Adapter Tool.

Human brain mapping
Volumetric assessments of the hippocampus and other brain structures during childhood provide useful indices of brain development and correlates of cognitive functioning in typically and atypically developing children. Automated methods such as FreeS...