Multi-atlas based pathological stratification of D-TGA congenital heart disease

@article{Zuluaga2014MultiatlasBP,
  title={Multi-atlas based pathological stratification of D-TGA congenital heart disease},
  author={Maria A. Zuluaga and Alex F. Mendelson and Manuel Jorge Cardoso and Andrew Mayall Taylor and S{\'e}bastien Ourselin},
  journal={2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)},
  year={2014},
  pages={109-112}
}
One of the main sources of error in multi-atlas segmentation propagation approaches comes from the use of atlas databases that are morphologically dissimilar to the target image. In this work, we exploit the segmentation errors associated with poor atlas selection to build a computer-aided diagnosis (CAD) system for pathological classification in post-operative dextro-transposition of the great arteries (d-TGA). The proposed approach extracts a set of features, which describe the quality of a… 

Figures from this paper

Multi-atlas synthesis for computer assisted diagnosis: Application to cardiovascular diseases

The aim of this work is to exploit the morphological dissimilarities between atlas databases and pathological images to diagnose the underlying clinical condition, while avoiding the dependence on labelled images.

Multi-atlas segmentation of biomedical images: A survey

Prediction of Heart Disease Using Naïve bayes and Image Processing

The study with respect to totally extraordinary arrangement systems utilized for anticipating the opportunity dimension of each individual bolstered age, sexual orientation, constrain per unit zone, cholesterol, beat rate will utilize naïve bayes and image processing to predict the heart disease efficiently.

References

SHOWING 1-6 OF 6 REFERENCES

Multi-atlas Propagation Whole Heart Segmentation from MRI and CTA Using a Local Normalised Correlation Coefficient Criterion

This work presents a fully automated method for the segmentation of the whole heart and the great vessels from 3D images based on a muti-atlas propagation segmentation scheme, that has been proven to be succesful in brain segmentation.

Automatic Multi-model-Based Segmentation of the Left Atrium in Cardiac MRI Scans

Model-based segmentation approaches have been proven to produce very accurate segmentation results while simultaneously providing an anatomic labeling for the segmented structures. However,

Learning from Only Positive and Unlabeled Data to Detect Lesions in Vascular CT Images

A new algorithm capable of detecting both calcified and non-calcified plaques in CT images is presented, which is comparable to state-of-the-art supervised methods, and the performance can improve after additional iterations.

A Grouping Principle and Four Applications

This paper shows that the Helmholtz principle is fully general and can be extended to a grouping by any quality and treats as an illustration the alignments of objects, their grouping by color and by size, and the vicinity gestalt (clusters).