Since the discovery of the X-ray radiation by Wilhelm Conrad Roentgen in 1895, the field of medical imaging has developed into a huge scientific discipline. The analysis of patient data acquired by current image modalities, such as computerized tomography (CT), magnetic resonance tomography (MRT), positron emission tomography (PET), or ultrasound (US), offers previously unattained opportunities for diagnosis, therapy planning, and therapy assessment. Medical Image Processing is essential to leverage this increasing amount of data and to explore and present the contained information in a way suitable for the specific medical task. In this tutorial, we will approach the analysis and visualization of medical image data in an explorative manner. In particular, we will visually construct the Image Processing algorithms using the popular graphical data-flow builder MeVisLab, which is available as a free download for noncommercial research. We felt that it could be more interesting for the reader to see and explore examples of medical Image Processing that go beyond simple image enhancements. The part of exploration, to inspect medical image data and experiment with image-processing pipelines, requires software that encourages this kind of visual exploration.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Cost-Optimal Caching for D2D Networks With User Mobility: Modeling, Analysis, and Computational Approaches - 2018ABSTRACT:Caching well-liked files at the user equipments (UEs) provides an efficient way to alleviate
PROJECT TITLE :Design, Analysis, and Implementation of ARPKI: An Attack-Resilient Public-Key Infrastructure - 2018ABSTRACT:This Transport Layer Security (TLS) Public-Key Infrastructure (PKI) is based on a weakest-link security
PROJECT TITLE : Dwt based medical image fusion with maximum Local extreme - 2016 ABSTRACT: In clinical applications fusion of images plays a vital role for best diagnosis. Here computed tomography(CT) image provides best info
PROJECT TITLE : MLP neural network classifier for medical image segmentation - 2016 ABSTRACT: The selection of a segmentation methodology depends on several concerns, particularly the character of the image, the primitives
PROJECT TITLE : Novel Example Based Method for Super-Resolution and Denoising of Medical Images - 2014 ABSTRACT: In this paper, we have a tendency to propose a completely unique example-based mostly method for denoising and

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry