AIMC Topic: Neural Networks, Computer

Clear Filters Showing 19211 to 19220 of 31376 articles

Automated classification of urinary stones based on microcomputed tomography images using convolutional neural network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: The classification of urinary stones is important prior to treatment because the treatments depend on three types of urinary stones, i.e., calcium, uric acid, and mixture stones. We have developed an automatic approach for the classification...

Using conditional generative adversarial networks to reduce the effects of latency in robotic telesurgery.

Journal of robotic surgery
The introduction of surgical robots brought about advancements in surgical procedures. The applications of remote telesurgery range from building medical clinics in underprivileged areas, to placing robots abroad in military hot-spots where accessibi...

Segmentation of cellular patterns in confocal images of melanocytic lesions in vivo via a multiscale encoder-decoder network (MED-Net).

Medical image analysis
In-vivo optical microscopy is advancing into routine clinical practice for non-invasively guiding diagnosis and treatment of cancer and other diseases, and thus beginning to reduce the need for traditional biopsy. However, reading and analysis of the...

ELNet:Automatic classification and segmentation for esophageal lesions using convolutional neural network.

Medical image analysis
Automatic and accurate esophageal lesion classification and segmentation is of great significance to clinically estimate the lesion statuses of the esophageal diseases and make suitable diagnostic schemes. Due to individual variations and visual simi...

Theoretical analysis and experimental validation of volume bias of soft Dice optimized segmentation maps in the context of inherent uncertainty.

Medical image analysis
The clinical interest is often to measure the volume of a structure, which is typically derived from a segmentation. In order to evaluate and compare segmentation methods, the similarity between a segmentation and a predefined ground truth is measure...

Efficient and Robust Instrument Segmentation in 3D Ultrasound Using Patch-of-Interest-FuseNet with Hybrid Loss.

Medical image analysis
Instrument segmentation plays a vital role in 3D ultrasound (US) guided cardiac intervention. Efficient and accurate segmentation during the operation is highly desired since it can facilitate the operation, reduce the operational complexity, and the...

Modelling the effects of transcranial alternating current stimulation on the neural encoding of speech in noise.

NeuroImage
Transcranial alternating current stimulation (tACS) can non-invasively modulate neuronal activity in the cerebral cortex, in particular at the frequency of the applied stimulation. Such modulation can matter for speech processing, since the latter in...

DeepResp: Deep learning solution for respiration-induced B fluctuation artifacts in multi-slice GRE.

NeuroImage
Respiration-induced B fluctuation corrupts MRI images by inducing phase errors in k-space. A few approaches such as navigator have been proposed to correct for the artifacts at the expense of sequence modification. In this study, a new deep learning ...

Improving CNN training on endoscopic image data by extracting additionally training data from endoscopic videos.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In this work we present a technique to deal with one of the biggest problems for the application of convolutional neural networks (CNNs) in the area of computer assisted endoscopic image diagnosis, the insufficient amount of training data. Based on p...