Reference Based Color Transfer for Medical Volume Rendering

10/14/2022
by   Sudarshan Devkota, et al.
0

The benefits of medical imaging are enormous. Medical images provide considerable amounts of anatomical information and this facilitates medical practitioners in performing effective disease diagnosis and deciding upon the best course of medical treatment. A transition from traditional monochromatic medical images like CT scans, X-Rays or MRI images to a colored 3D representation of the anatomical structure further enhances the capabilities of medical professionals in extracting valuable medical information. The proposed framework in our research starts with performing color transfer by finding deep semantic correspondence between two medical images: a colored reference image, and a monochromatic CT scan or an MRI image. We extend this idea of reference-based colorization technique to perform colored volume rendering from a stack of grayscale medical images. Furthermore, we also propose to use an effective reference image recommendation system to aid in the selection of good reference images. With our approach, we successfully perform colored medical volume visualization and essentially eliminate the painstaking process of user interaction with a transfer function to obtain color and opacity parameters for volume rendering.

READ FULL TEXT

page 1

page 4

page 5

page 6

page 7

page 8

page 9

research
11/11/2016

Effective sparse representation of X-Ray medical images

Effective sparse representation of X-Ray medical images within the conte...
research
09/16/2014

A Combined Method Of Fractal And GLCM Features For MRI And CT Scan Images Classification

Fractal analysis has been shown to be useful in image processing for cha...
research
08/16/2021

Semi-Supervised Siamese Network for Identifying Bad Data in Medical Imaging Datasets

Noisy data present in medical imaging datasets can often aid the develop...
research
06/18/2008

Neural networks in 3D medical scan visualization

For medical volume visualization, one of the most important tasks is to ...
research
05/05/2021

Bayesian Logistic Shape Model Inference: application to cochlea image segmentation

Incorporating shape information is essential for the delineation of many...
research
10/07/2020

Learning Binary Semantic Embedding for Histology Image Classification and Retrieval

With the development of medical imaging technology and machine learning,...
research
04/06/2020

Multimodal Medical Volume Colorization from 2D Style

Colorization involves the synthesis of colors on a target image while pr...

Please sign up or login with your details

Forgot password? Click here to reset