AIMC Topic: Brain

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Predicting chemo-brain in breast cancer survivors using multiple MRI features and machine-learning.

Magnetic resonance in medicine
PURPOSE: Breast cancer (BC) is the most common cancer in women worldwide. There exist various advanced chemotherapy drugs for BC; however, chemotherapy drugs may result in brain damage during treatment. When a patient's brain is changed in response t...

[Interest of robotic stereotactic radiosurgery in the management of brain metastases: Results of a retrospective, single center analysis].

Neuro-Chirurgie
PURPOSE: The management of malignant brain metastases becomes a main issue for the treatment of patients, because of the survival extension related to the improvement in systemic treatments. Robotic stereotactic radiosurgery (RSR) is a new approach i...

HyperDense-Net: A Hyper-Densely Connected CNN for Multi-Modal Image Segmentation.

IEEE transactions on medical imaging
Recently, dense connections have attracted substantial attention in computer vision because they facilitate gradient flow and implicit deep supervision during training. Particularly, DenseNet that connects each layer to every other layer in a feed-fo...

[The body, art and the machines].

Tidsskrift for den Norske laegeforening : tidsskrift for praktisk medicin, ny raekke

Resting-state Functional Connectivity and Deception: Exploring Individualized Deceptive Propensity by Machine Learning.

Neuroscience
Individuals show marked variability in determining to be honest or deceptive in daily life. A large number of studies have investigated the neural substrates of deception; however, the brain networks contributing to the individual differences in dece...

Recognizing Brain States Using Deep Sparse Recurrent Neural Network.

IEEE transactions on medical imaging
Brain activity is a dynamic combination of different sensory responses and thus brain activity/state is continuously changing over time. However, the brain's dynamical functional states recognition at fast time-scales in task fMRI data have been rare...

Deep neural network predicts emotional responses of the human brain from functional magnetic resonance imaging.

NeuroImage
An artificial neural network with multiple hidden layers (known as a deep neural network, or DNN) was employed as a predictive model (DNN) for the first time to predict emotional responses using whole-brain functional magnetic resonance imaging (fMRI...

Evaluating performance of neural codes in model neural communication networks.

Neural networks : the official journal of the International Neural Network Society
Information needs to be appropriately encoded to be reliably transmitted over physical media. Similarly, neurons have their own codes to convey information in the brain. Even though it is well-known that neurons exchange information using a pool of s...

Deep Learning for MR Angiography: Automated Detection of Cerebral Aneurysms.

Radiology
Purpose To develop and evaluate a supportive algorithm using deep learning for detecting cerebral aneurysms at time-of-flight MR angiography to provide a second assessment of images already interpreted by radiologists. Materials and Methods MR images...