Skip to search formSkip to main contentSkip to account menu

MeVisLab

MeVisLab is a cross-platform application framework for medical image processing and scientific visualization. It includes advanced algorithms for… 
Wikipedia (opens in a new tab)

Related topics

Related topics

35 relations
2D computer graphics3D computer graphics3DSlicerApplication framework

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Client/Server Based Online Environment for Manual Segmentation of Medical Images
Segmentation is a key step in analyzing and processing medical images. Due to the low fault tolerance in medical imaging, manual… 
2017
2017
Produzione di contenuti grafici interattivi mediante strumenti di editing visuale = Production of interactive graphics content through visual editing tools
PROGETTAZIONE E SVILUPPO DI STRUMENTI DI EDITING PER LA RAPPRESENTAZIONE INTERATTIVA DI CONTENUTI OLOGRAFICI 
2016
2016
A generic module interface in MeVisLab using OpenIGTLink for defining iterative communication workflows among robotic devices
The goal of this work is to provide a software platform that can seamlessly plug-in and plug-out software and hardware components… 
2015
2015
Automatic Semantic Labelling of Urban Areas using a rule-based approach and realized with MeVisLab
The article is about a project done at the ITC faculty of the University of Twente. It describes a rule-based system and the… 
2013
2013
1090 Extracting MRI Sequence Response Kernels from Generalized Extended Phase Graph Simulations
Introduction and Motivation: The Extended Phase Graph algorithm is a tool commonly used to predict echo times and echo amplitudes… 
2013
2013
Blood vessel segmentation for neck and head computed tomography angiography
This thesis presents tests and discussions evaluating different methods for doing automatic or semi automatic blood vessel… 
2012
2012
Segmentation and 3-Dimensional Reconstruction of Liver using MeVisLab
의료기기 및 진단 기술의 발달로 신체 장기의 이식에 대한 성공률이 향상되었으며 특히 간 기능 장애에 의한 간 이식이 늘어나는 추세이다. 영상처리 및 분석의 발달로 간 이식을 위한 간의 체적을 구하는 방법들이 정확성과 효율성이 높아졌다. 본 논문은 각 알고리즘들의 신속한 비교 및 분석, 빠른 프로토타입 개발에 효과적인 MeVisLab을 사용하여 간 영역을 분할하고 재구성하였다. 원본 영상에 문턱치 값 적용과 영역 확장법을 적용하여 간 영역을 분할하고 Morphology와 구멍 채우기, 관심영역 설정으로 노이즈 및 불필요한 객체를 제거하여 간을 분할하였다. MeVisLab의 사용으로 높은 시간적 효율과 다양한 비교 및 분석 모듈 사용 방법을 제시하여 의료영상처리 연구의 저변 확대에 기여하리라 판단된다. 
Review
2010
Review
2010
Automatic Transfer Function Specification for Visual Emphasis of Coronary Artery Plaque
Cardiovascular imaging with current multislice spiral computed tomography (MSCT) technology enables a non‐invasive evaluation of… 
2010
2010
Fast and Smooth Interactive Segmentation of Medical Images Using Variational Interpolation
We present a fast and interactive segmentation method for medical images that allows a smooth reconstruction of an object's… 
2009
2009
Processing, Visualization and Analysis of Medical Images of the Heart: An Example of Fast Prototyping Using MeVisLab
Developing and testing new algorithms for medical imaging processing can be a tiresome task as it often requires an additional… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)