Amanote Research

Amanote Research

    RegisterSign In

Evaluation of Gastric Diseases Using Segmentation RGB Interface in Video Endoscopy Images

International Journal of Advanced Engineering, Management and Science
doi 10.22161/ijaems.4.6.8
Full Text
Open PDF
Abstract

Available in full text

Date

January 1, 2018

Authors
Sandra Luz Mendoza-TrejoVíctor Manuel Ruiz-MartinezJosé Ernesto Domínguez-Herrera
Publisher

AI Publications


Related search

Detecting Gastric Cancer From Video Images Using Convolutional Neural Networks

Digestive Endoscopy
Nuclear MedicineRadiologyImagingGastroenterology
2018English

Evaluation of Gastric Disease With Capsule Endoscopy

Clinical Endoscopy
MedicineNuclear MedicineRadiologyImagingGastroenterology
2018English

Automatic Video Segmentation and Object Tracking With Real-Time RGB-D Data

2014English

Comparison of Segmentation Framework on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using RGB and HSV Color Spaces

Journal of Biomedical Engineering and Medical Imaging
2015English

Tree, Shrub, and Grass Classification Using Only RGB Images

Remote Sensing
EarthPlanetary Sciences
2020English

Video Capsule Endoscopy

Basrah Journal of Surgery
2006English

Automated Segmentation of Iris Images Using Visible Wavelength Face Images

2011English

Accurate Localization of 3D Objects From RGB-D Data Using Segmentation Hypotheses

2013English

Segmentation of MR Images Using Neural Nets

1991English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy