AIMC Topic: Neural Networks, Computer

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Efficient and robust cell detection: A structured regression approach.

Medical image analysis
Efficient and robust cell detection serves as a critical prerequisite for many subsequent biomedical image analysis methods and computer-aided diagnosis (CAD). It remains a challenging task due to touching cells, inhomogeneous background noise, and l...

A survey on deep learning in medical image analysis.

Medical image analysis
Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 ...

Efficient hardware implementation of the subthalamic nucleus-external globus pallidus oscillation system and its dynamics investigation.

Neural networks : the official journal of the International Neural Network Society
Modeling and implementation of the nonlinear neural system with physiologically plausible dynamic behaviors are considerably meaningful in the field of computational neuroscience. This study introduces a novel hardware platform to investigate the dyn...

Phenomenological network models: Lessons for epilepsy surgery.

Epilepsia
The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational m...

Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging.

Computational and mathematical methods in medicine
Free-breathing cardiac magnetic resonance (CMR) imaging has short examination time with high reproducibility. Detection of the end-diastole and the end-systole frames of the free-breathing cardiac magnetic resonance, supplemented by visual identifica...

Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction.

Journal of chemical information and modeling
The task of learning an expressive molecular representation is central to developing quantitative structure-activity and property relationships. Traditional approaches rely on group additivity rules, empirical measurements or parameters, or generatio...

A multivariate extension of mutual information for growing neural networks.

Neural networks : the official journal of the International Neural Network Society
Recordings of neural network activity in vitro are increasingly being used to assess the development of neural network activity and the effects of drugs, chemicals and disease states on neural network function. The high-content nature of the data der...

Few-shot learning in deep networks through global prototyping.

Neural networks : the official journal of the International Neural Network Society
Training a deep convolution neural network (CNN) to succeed in visual object classification usually requires a great number of examples. Here, starting from such a pre-learned CNN, we study the task of extending the network to classify additional cat...

Automated diagnosis of prostate cancer in multi-parametric MRI based on multimodal convolutional neural networks.

Physics in medicine and biology
Automated methods for prostate cancer (PCa) diagnosis in multi-parametric magnetic resonance imaging (MP-MRIs) are critical for alleviating requirements for interpretation of radiographs while helping to improve diagnostic accuracy (Artan et al 2010 ...

Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
INTRODUCTION: To develop real-time image processing for image-guided radiotherapy, we evaluated several neural network models for use with different imaging modalities, including X-ray fluoroscopic image denoising.