AIMC Topic:
Image Interpretation, Computer-Assisted

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Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

Journal of neuroscience methods
BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of AD, and existing studies have...

Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI.

Schizophrenia research
Although regional brain deficits have been demonstrated in schizophrenia patients by structural MRI studies, one important question that remains largely unanswered is whether the complex and subtle deficits revealed by MRI could be used as objective ...

Construction of a system using a deep learning algorithm to count cell numbers in nanoliter wells for viable single-cell experiments.

Scientific reports
For single-cell experiments, it is important to accurately count the number of viable cells in a nanoliter well. We used a deep learning-based convolutional neural network (CNN) on a large amount of digital data obtained as microscopic images. The tr...

Learning non-linear patch embeddings with neural networks for label fusion.

Medical image analysis
In brain structural segmentation, multi-atlas strategies are increasingly being used over single-atlas strategies because of their ability to fit a wider anatomical variability. Patch-based label fusion (PBLF) is a type of such multi-atlas approaches...

Automatic Target Recognition Strategy for Synthetic Aperture Radar Images Based on Combined Discrimination Trees.

Computational intelligence and neuroscience
A strategy is introduced for achieving high accuracy in synthetic aperture radar (SAR) automatic target recognition (ATR) tasks. Initially, a novel pose rectification process and an image normalization process are sequentially introduced to produce i...

Early Diagnosis of Alzheimer's Disease Based on Resting-State Brain Networks and Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Computerized healthcare has undergone rapid development thanks to the advances in medical imaging and machine learning technologies. Especially, recent progress on deep learning opens a new era for multimedia based clinical decision support. In this ...

Looking for Alzheimer's Disease morphometric signatures using machine learning techniques.

Journal of neuroscience methods
BACKGROUND: We present our results in the International challenge for automated prediction of MCI from MRI data. We evaluate the performance of MRI-based neuromorphometrics features (nMF) in the classification of Healthy Controls (HC), Mild Cognitive...

Correlation Filters for Detection of Cellular Nuclei in Histopathology Images.

Journal of medical systems
UNLABELLED: Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for ...

Machine Learning in Radiology: Applications Beyond Image Interpretation.

Journal of the American College of Radiology : JACR
Much attention has been given to machine learning and its perceived impact in radiology, particularly in light of recent success with image classification in international competitions. However, machine learning is likely to impact radiology outside ...

Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning.

Scientific reports
Prostate cancer (PCa) is a major cause of death since ancient time documented in Egyptian Ptolemaic mummy imaging. PCa detection is critical to personalized medicine and varies considerably under an MRI scan. 172 patients with 2,602 morphologic image...