scholarly journals MATITK: EXTENDING MATLAB WITH ITK

2005 ◽  
Author(s):  
Vincent Chu ◽  
Ghassan Hamarneh
Keyword(s):  
Image Analysis ◽  
Open Source ◽  
Medical Image ◽  
Image Data ◽  
Source Image ◽  
Research Environment ◽  
Low Level ◽  
Medical Image Data

To facilitate the analysis of medical image data in research environment, MATITK is developed to allow ITK algorithms to be called in MATLAB. ITK is a powerful open-source image analysis toolkit, but it requires the knowledge of C++ to use it. With the help of MATITK, researchers familiar with MATLAB can harness the power of ITK without learning C++ and worrying about low-level programming issues. A common set of C++ classes have also been produced to allow future ITK methods to be added to MATITK therefore callable in MATLAB without the bothersome translation between MATLAB and ITK.

scholarly journals Cerebral Cortical Thickness Estimation using the TINA Open-Source Image Analysis Environment

2005 ◽  
Author(s):  
Marietta Scott ◽  
Paul A. Bromiley ◽  
Neil A. Thacker
Keyword(s):  
Image Analysis ◽  
Open Source ◽  
Cortical Thickness ◽  
Medical Image ◽  
Medical Image Analysis ◽  
Magnetic Resonance Images ◽  
Source Image ◽  
Thickness Estimation ◽  
Analysis Environment

This paper gives an overview of the use and development of the TINA open-source medical image analysis environment, with respect to the determination of human cerebral cortical thickness estimation from magnetic resonance images. The ultimate aim of TINA is to provide a validated system where the source code and datasets are freely available in order to allow peer-validation of published results.

scholarly journals Design and Implementation of Compressed Medical Data over an Authenticated Secured

2020 ◽  
Vol 9 (3) ◽  
pp. 1543-1548
Keyword(s):  
Medical Image ◽  
Research Work ◽  
Health Sector ◽  
Image Data ◽  
Medical Data ◽  
Information Network ◽  
Design And Implementation ◽  
Simulation Results ◽  
Medical Image Data ◽  
Secure Transmission

Ideally, secure transmission of medical image data is one of the major challenges in health sector. The National Health Information Network has to protect the data in confidential manner. Storage is also one of the basic concern along with secure transmission. In this paper we propose an algorithm that supports confidentiality, authentication and integrity implementation of the scrambled data before transmitting on the communication medium. Before communication the data is compressed while keeping data encrypted. The research work demonstrate with simulation results. The results shows that the proposed work effectively maintains confidentiality, authentication and integrity. The experimental results evaluated medical image quality like PSNR, MSE, SC, and NAEetc.

Similarity Searching of Medical Image Data in Distributed Systems

2012 ◽  
pp. 58-77
Author(s):  
Amalia Charisi ◽  
Panagiotis Korvesis ◽  
Vasileios Megalooikonomou
Keyword(s):  
Distributed Systems ◽  
Image Retrieval ◽  
Medical Image ◽  
Image Data ◽  
Medical Data ◽  
Similarity Searching ◽  
Network Bandwidth ◽  
Local Site ◽  
Distributed Index ◽  
Medical Image Data

In this paper, the authors propose a method for medical image retrieval in distributed systems to facilitate telemedicine. The proposed framework can be used by a network of healthcare centers, where some can be remotely located, assisting in diagnosis without the necessary transfer of patients. Security and confidentiality issues of medical data are expected, which are handled at the local site following the procedures and protocols of each institution. To make the search more effective, the authors introduce a distributed index based on features that are extracted from each image. Considering network bandwidth limitations and other restrictions that are associated with handling medical data, the images are processed locally and a pointer is distributed in the network. For the distribution of this pointer, the authors propose a function that maps the pointer of each image to a node with similar contents.

Sign in / Sign up

Export Citation Format

Share Document