AIMC Topic: Deep Learning

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Depth with nonlinearity creates no bad local minima in ResNets.

Neural networks : the official journal of the International Neural Network Society
In this paper, we prove that depth with nonlinearity creates no bad local minima in a type of arbitrarily deep ResNets with arbitrary nonlinear activation functions, in the sense that the values of all local minima are no worse than the global minimu...

A deep learning based pipeline for optical coherence tomography angiography.

Journal of biophotonics
Optical coherence tomography angiography (OCTA) is a relatively new imaging modality that generates microvasculature map. Meanwhile, deep learning has been recently attracting considerable attention in image-to-image translation, such as image denois...

Automated diagnosis of ear disease using ensemble deep learning with a big otoendoscopy image database.

EBioMedicine
BACKGROUND: Ear and mastoid disease can easily be treated by early detection and appropriate medical care. However, short of specialists and relatively low diagnostic accuracy calls for a new way of diagnostic strategy, in which deep learning may pla...

A feature agnostic approach for glaucoma detection in OCT volumes.

PloS one
Optical coherence tomography (OCT) based measurements of retinal layer thickness, such as the retinal nerve fibre layer (RNFL) and the ganglion cell with inner plexiform layer (GCIPL) are commonly employed for the diagnosis and monitoring of glaucoma...

Next generation research applications for hybrid PET/MR and PET/CT imaging using deep learning.

European journal of nuclear medicine and molecular imaging
INTRODUCTION: Recently there have been significant advances in the field of machine learning and artificial intelligence (AI) centered around imaging-based applications such as computer vision. In particular, the tremendous power of deep learning alg...

Scale-space approximated convolutional neural networks for retinal vessel segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Retinal fundus images are widely used to diagnose retinal diseases and can potentially be used for early diagnosis and prevention of chronic vascular diseases and diabetes. While various automatic retinal vessel segmentation...

Brain tumor classification using deep CNN features via transfer learning.

Computers in biology and medicine
Brain tumor classification is an important problem in computer-aided diagnosis (CAD) for medical applications. This paper focuses on a 3-class classification problem to differentiate among glioma, meningioma and pituitary tumors, which form three pro...

Utilization of Artificial Intelligence in Echocardiography.

Circulation journal : official journal of the Japanese Circulation Society
Echocardiography has a central role in the diagnosis and management of cardiovascular disease. Precise and reliable echocardiographic assessment is required for clinical decision-making. Even if the development of new technologies (3-dimentional echo...

Improved Deep Learning Network Based in combination with Cost-sensitive Learning for Early Detection of Ovarian Cancer in Color Ultrasound Detecting System.

Journal of medical systems
With the development of theories and technologies in medical imaging, most of the tumors can be detected in the early stage. However, the nature of ovarian cysts lacks accurate judgement, leading to that many patients with benign nodules still need F...