AIMC Topic: Neural Networks, Computer

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Lung segmentation method with dilated convolution based on VGG-16 network.

Computer assisted surgery (Abingdon, England)
Lung cancer has become one of the life-threatening killers. Lung disease need to be assisted by CT images taken doctor's diagnosis, and the segmented CT image of the lung parenchyma is the first step to help doctor diagnosis. For the problem of accur...

Challenges Facing the Detection of Colonic Polyps: What Can Deep Learning Do?

Medicina (Kaunas, Lithuania)
Colorectal cancer (CRC) is one of the most common causes of cancer mortality in the world. The incidence is related to increases with age and western dietary habits. Early detection through screening by colonoscopy has been proven to effectively redu...

An Intelligent Segmentation and Diagnosis Method for Diabetic Retinopathy Based on Improved U-NET Network.

Journal of medical systems
Due to insufficient samples, the generalization performance of deep network is insufficient. In order to solve this problem, an improved U-net based image automatic segmentation and diagnosis algorithm was proposed, in which the max-pooling operation...

Flexible model of network embedding.

Scientific reports
There has lately been increased interest in describing complex systems not merely as single networks but rather as collections of networks that are coupled to one another. We introduce an analytically tractable model that enables one to connect two l...

Neural-network classification of cardiac disease from P cardiovascular magnetic resonance spectroscopy measures of creatine kinase energy metabolism.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: The heart's energy demand per gram of tissue is the body's highest and creatine kinase (CK) metabolism, its primary energy reserve, is compromised in common heart diseases. Here, neural-network analysis is used to test whether noninvasive...

A modeling and machine learning approach to ECG feature engineering for the detection of ischemia using pseudo-ECG.

PloS one
Early detection of coronary heart disease (CHD) has the potential to prevent the millions of deaths that this disease causes worldwide every year. However, there exist few automatic methods to detect CHD at an early stage. A challenge in the developm...

An investigation of CNN models for differentiating malignant from benign lesions using small pathologically proven datasets.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Cancer has been one of the most threatening diseases to human health. There have been many efforts devoted to the advancement of radiology and transformative tools (e.g. non-invasive computed tomographic or CT imaging) to detect cancer in early stage...

Early prediction of epileptic seizures using a long-term recurrent convolutional network.

Journal of neuroscience methods
BACKGROUND: A seizure prediction system can detect seizures prior to their occurrence and allow clinicians to provide timely treatment for patients with epilepsy. Research on seizure prediction has progressed from signal processing analyses to machin...

Automatic diagnosis of fungal keratitis using data augmentation and image fusion with deep convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Fungal keratitis is caused by inflammation of the cornea that results from infection by fungal organisms. The lack of an early effective diagnosis often results in serious complications even blindness. Confocal microscopy i...

Recognition of peripheral blood cell images using convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Morphological analysis is the starting point for the diagnostic approach of more than 80% of hematological diseases. However, the morphological differentiation among different types of normal and abnormal peripheral blood c...