ANGELIN JEBA J

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering, Computer Networks and Communications, Signal Processing, Computer Vision and Pattern Recognition

Scopus Publications

Modified CNN Architecture for Efficient Classification of Glioma Brain Tumour
J. Angelin Jeba, S. Nirmala Devi, and M. Meena
Informa UK Limited



Shape Description of FDG uptakes in Pre and Postoperative fused PET/CT Images
J. Angelin Jeba and S. Nirmala Devi
IEEE
Automatic object recognition with shape descriptors help to interact with the real-time environment. This paper describes the shape analysis of radioactivity Fluoro Deoxy Glucose (FDG) uptakes present in pre and postoperative stages of Fused PET/CT images using shape feature extraction approach. Shape features are invariant to various affine transformations such as translation, rotational, flipped, scale, etc., are more robust for shape analysis. Geometrical properties of the FDG uptakes are extracted at various levels of spatial resolution by hierarchical Kdabstraction from the segmented PET/CT images. Rotational invariants considered are the Zernike moments magnitudes and the shape signatures of Fourier descriptors are investigated. The discrimination power of features between pre and post-operative images is examined and evaluated.


Efficient graph cut optimization using hybrid kernel functions for segmentation of FDG uptakes in fused PET/CT images
J. Angelin Jeba and S. Nirmala Devi
Elsevier BV