Topics

Automatic Symmetry Detection From Brain MRI Based on a 2-Channel Convolutional Neural Network.

07:00 EST 28th November 2019 | BioPortfolio

Summary of "Automatic Symmetry Detection From Brain MRI Based on a 2-Channel Convolutional Neural Network."

Symmetry detection is a method to extract the ideal mid-sagittal plane (MSP) from brain magnetic resonance (MR) images, which can significantly improve the diagnostic accuracy of brain diseases. In this article, we propose an automatic symmetry detection method for brain MR images in 2-D slices based on a 2-channel convolutional neural network (CNN). Different from the existing detection methods that mainly rely on the local image features (gradient, edge, etc.) to determine the MSP, we use a CNN-based model to implement the brain symmetry detection, which does not require any local feature detections and feature matchings. By training to learn a wide variety of benchmarks in the brain images, we can further use a 2-channel CNN to evaluate the similarity between the pairs of brain patches, which are randomly extracted from the whole brain slice based on a Poisson sampling. Finally, a scoring and ranking scheme is used to identify the optimal symmetry axis for each input brain MR slice. Our method was evaluated in 2166 artificial synthesized brain images and 3064 collected in vivo MR images, which included both healthy and pathological cases. The experimental results display that our method achieves excellent performance for symmetry detection. Comparisons with the state-of-the-art methods also demonstrate the effectiveness and advantages for our approach in achieving higher accuracy than the previous competitors.

Affiliation

Journal Details

This article was published in the following journal.

Name: IEEE transactions on cybernetics
ISSN: 2168-2275
Pages:

Links

DeepDyve research library

PubMed Articles [26320 Associated PubMed Articles listed on BioPortfolio]

Orthogonal convolutional neural networks for automatic sleep stage classification based on single-channel EEG.

In recent years, several automatic sleep stage classification methods based on convolutional neural networks (CNN) by learning hierarchical feature representation automatically from raw EEG data have ...

The Asymmetric-Distance Metrics for Decoding of Convolutional Codes in Diffusion-Based Molecular Communications.

In this paper, we focus on the channel coding for diffusion-based molecular communications (MC) with information conveyed in the time of molecules released. The symbol error probability (SEP) is theor...

A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset.

The automatic recognition of human falls is currently an important topic of research for the computer vision and artificial intelligence communities. In image analysis, it is common to use a vision-ba...

A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning.

Detection of pulmonary nodules is an important aspect of an automatic detection system. Incomputer-aided diagnosis (CAD) systems, the ability to detect pulmonary nodules is highly important, which pla...

Deep convolutional neural network for classification of sleep stages from single-channel EEG signals.

Using a smart method for automatic diagnosis in medical applications, such as sleep stage classification is considered as one of the important challenges of the last few years which can replace the ti...

Clinical Trials [10969 Associated Clinical Trials listed on BioPortfolio]

Impact of Automatic Polyp Detection System on Adenoma Detection Rate

In recent years, with the continuous development of artificial intelligence, automatic polyp detection systems have shown its potential in increasing the colorectal lesions. Yet, whether t...

Deep-Learning for Automatic Polyp Detection During Colonoscopy

The primary objective of this study is to examine the role of machine learning and computer aided diagnostics in automatic polyp detection and to determine whether a combination of colonos...

Automatic Segmentation of Polycystic Liver

Assessing the volume of the liver before surgery, predicting the volume of liver remaining after surgery, detecting primary or secondary lesions in the liver parenchyma are common applicat...

Smartband/Smartphone-based Automatic Smoking Detection and Real Time Mindfulness Intervention

To determine treatment fidelity for a smartband/smartphone-based smoking monitoring, notification and brief mindfulness intervention.

A Multi-center RCT Study on the Efficacy and Mechanism of Multi-channel tDCS in Rehabilitation of Cognitive Function After Stroke

This clinical RCT study intends to combined different forms of multi-channel tDCS with the routine cognitive training process to treat patients with post-stroke cognitive dysfunction. The...

Medical and Biotech [MESH] Definitions

A class of unsegmented helminths with fundamental bilateral symmetry and secondary triradiate symmetry of the oral and esophageal structures. Many species are parasites.

Data processing largely performed by automatic means.

Detection of drugs that have been abused, overused, or misused, including legal and illegal drugs. Urine screening is the usual method of detection.

Abnormally rapid heartbeats originating from one or more automatic foci (nonsinus pacemakers) in the HEART ATRIUM but away from the SINOATRIAL NODE. Unlike the reentry mechanism, automatic tachycardia speeds up and slows down gradually. The episode is characterized by a HEART RATE between 135 to less than 200 beats per minute and lasting 30 seconds or longer.

A voltage-gated sodium channel subtype that mediates the sodium ion PERMEABILITY of CARDIOMYOCYTES. Defects in the SCN5A gene, which codes for the alpha subunit of this sodium channel, are associated with a variety of CARDIAC DISEASES that result from loss of sodium channel function.

Quick Search


DeepDyve research library

Relevant Topics

Radiology
Radiology is the branch of medicine that studies imaging of the body; X-ray (basic, angiography, barium swallows), ultrasound, MRI, CT and PET. These imaging techniques can be used to diagnose, but also to treat a range of conditions, by allowing visuali...

Antiretroviral therapy
Standard antiretroviral therapy (ART) consists of the combination of at least three antiretroviral (ARV) drugs to maximally suppress the HIV virus and stop the progression of HIV disease. Huge reductions have been seen in rates of death and suffering whe...


Searches Linking to this Article