AIMC Topic: Brain

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Automatic attenuation map estimation from SPECT data only for brain perfusion scans using convolutional neural networks.

Physics in medicine and biology
In clinical brain SPECT, correction for photon attenuation in the patient is essential to obtain images which provide quantitative information on the regional activity concentration per unit volume (kBq.[Formula: see text]). This correction generally...

MAMA Net: Multi-Scale Attention Memory Autoencoder Network for Anomaly Detection.

IEEE transactions on medical imaging
Anomaly detection refers to the identification of cases that do not conform to the expected pattern, which takes a key role in diverse research areas and application domains. Most of existing methods can be summarized as anomaly object detection-base...

Machine learning and bioinformatic analysis of brain and blood mRNA profiles in major depressive disorder: A case-control study.

American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics
This study analyzed gene expression messenger RNA data, from cases with major depressive disorder (MDD) and controls, using supervised machine learning (ML). We built on the methodology of prior studies to obtain more generalizable/reproducible resul...

Neuromorphic Binarized Polariton Networks.

Nano letters
The rapid development of artificial neural networks and applied artificial intelligence has led to many applications. However, current software implementation of neural networks is severely limited in terms of performance and energy efficiency. It is...

Two-Dimensional Stockwell Transform and Deep Convolutional Neural Network for Multi-Class Diagnosis of Pathological Brain.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Since the brain lesion detection and classification is a vital diagnosis task, in this paper, the problem of brain magnetic resonance imaging (MRI) classification is investigated. Recent advantages in machine learning and deep learning allows the res...

CTNN: A Convolutional Tensor-Train Neural Network for Multi-Task Brainprint Recognition.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Brainprint is a new type of biometric in the form of EEG, directly linking to intrinsic identity. Currently, most methods for brainprint recognition are based on traditional machine learning and only focus on a single brain cognition task. Due to the...

Deep learning based automatic diagnosis of first-episode psychosis, bipolar disorder and healthy controls.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Neuroimaging data driven machine learning based predictive modeling and pattern recognition has been attracted strongly attention in biomedical sciences. Machine learning based diagnosis techniques are widely applied in diagnosis of neurological dise...

Synthesizing CT images from MR images with deep learning: model generalization for different datasets through transfer learning.

Biomedical physics & engineering express
Replacing CT imaging with MR imaging for MR-only radiotherapy has sparked the interest of many scientists and is being increasingly adopted in radiation oncology. Although many studies have focused on generating CT images from MR images, only models ...

Neural state space alignment for magnitude generalization in humans and recurrent networks.

Neuron
A prerequisite for intelligent behavior is to understand how stimuli are related and to generalize this knowledge across contexts. Generalization can be challenging when relational patterns are shared across contexts but exist on different physical s...

Convolutional Neural Network-Based Deep Learning Model for Predicting Differential Suicidality in Depressive Patients Using Brain Generalized q-Sampling Imaging.

The Journal of clinical psychiatry
OBJECTIVE: Suicide is a priority health problem. Suicide assessment depends on imperfect clinician assessment with minimal ability to predict the risk of suicide. Machine learning/deep learning provides an opportunity to detect an individual at risk ...