Πλοήγηση ανά Θέμα "Wireless capsule endoscopy"
Αποτελέσματα 1-13 από 13
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An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy
(2017)Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with ... -
DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy
(2018)Wireless Capsule Endoscopy (WCE) is a noninvasive diagnostic technique enabling the inspection of the whole gastrointestinal (GI) tract by capturing and wirelessly transmitting thousands of color images. Proprietary software ... -
Enabling distributed summarization of wireless capsule endoscopy video
(2010)The introduction of distributed or parallel medical video processing is a constant growing need, because despite the large increase of modern workstations computational power, the amount of data in medical videos is growing ... -
EndoVAE: Generating Endoscopic Images with a Variational Autoencoder
(2022)The generalization performance of deep learning models is closely associated with the number and diversity of data available upon training. While in many applications there is a large number of data available in public, ... -
Enhanced CNN-Based gaze estimation on wireless capsule endoscopy images
(2021)Wireless capsule endoscopy (WCE) is a modality used for the non-invasive examination of the gastrointestinal (GI) tract. Physicians diagnose pathologies in images derived from Capsule Endoscopy (CE) using specific gaze ... -
Explainable Classification of Weakly Annotated Wireless Capsule Endoscopy Images Based on a Fuzzy Bag-of-Colour Features Model and Brain Storm Optimization
(2021)Wireless capsule endoscopy (WCE) constitutes a medical imaging technology developed for the endoscopic exploration of the gastrointestinal (GI) tract, whereas it provides a more comfortable examination method, in comparison ... -
Intelligent visual localization of wireless capsule endoscopes enhanced by color information
(2017)Wireless capsule endoscopy (WCE) is performed with a miniature swallowable endoscope enabling the visualization of the whole gastrointestinal (GI) tract. One of the most challenging problems in WCE is the localization of ... -
Look-behind fully convolutional neural network for computer-aided endoscopy
(2019)In this paper, we propose a novel Fully Convolutional Neural Network (FCN) architecture aiming to aid the detection of abnormalities, such as polyps, ulcers and blood, in gastrointestinal (GI) endoscopy images. The proposed ... -
MedGaze: Gaze Estimation on WCE Images Based on a CNN Autoencoder
(2019)The interpretation of medical images depends on physicians' experience. Over time, physicians develop their ability to examine the images, and this is usually reflected on gaze patterns they follow to observe visual cues, ... -
Robotic validation of visual odometry for wireless capsule endoscopy
(2016)Wireless capsule endoscopy (WCE) is the prime diagnostic modality for the small-bowel. It consists in a swallowable color camera that enables the visual detection and assessment of abnormalities, without patient discomfort. ... -
Towards the substitution of real with artificially generated endoscopic images for CNN training
(2019)The generalization performance in deep learning is linked to the size and the variations of the samples available during training. This is apparent in the domain of computer-aided gastrointestinal tract abnormality detection, ... -
Visual Localization of Wireless Capsule Endoscopes Aided by Artificial Neural Networks
(2017)Various modalities are used for the examination of the gastrointestinal (GI) tract. One such modality is Wireless Capsule Endoscopy (WCE), a non-invasive technique which consists of a swallowable color camera that enables ... -
Weakly-supervised Convolutional learning for detection of inflammatory gastrointestinal lesions
(2016)Graphic image annotations provide the necessary ground truth information for supervised machine learning in image-based computer-aided medical diagnosis. Performing such annotations is usually a time-consuming and ...