AIMC Topic: Image Interpretation, Computer-Assisted

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Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

Oncotarget
Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of dif...

A cross-sectional evaluation of meditation experience on electroencephalography data by artificial neural network and support vector machine classifiers.

Medicine
To quantitate the meditation experience is a subjective and complex issue because it is confounded by many factors such as emotional state, method of meditation, and personal physical condition. In this study, we propose a strategy with a cross-secti...

The Diagnostic Imagination in Radiology: Part 2.

Radiology management
Developing algorithms for the improve- ment of diagnostic care leverages tech- nologies and techniques developed across industries that are exponentially being improved, developed, and tested. Machine learning means extracting patterns not only from ...

MRI-based prostate cancer detection with high-level representation and hierarchical classification.

Medical physics
PURPOSE: Extracting the high-level feature representation by using deep neural networks for detection of prostate cancer, and then based on high-level feature representation constructing hierarchical classification to refine the detection results.

Breast osteoblastoma and recurrence after resection: Demonstration by color Doppler ultrasound.

Journal of X-ray science and technology
Osteoblastoma is a rare benign primary bone tumor, which occurs in any part of the skeleton. Extraskeletal osteoblastoma is rather rare. We presented an extremely rare case of extraskeletal osteoblastoma located in the breast. The tumor recurred 7 mo...