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Medical Imaging 2016
October 20-21, 2016
Volume 5, Issue 5(Suppl) OMICS J Radiol
ISSN: 2167-7964 ROA, an open access journal
conferenceseries .com
October 20-21, 2016 Chicago, USA
International Conference on
Medical Imaging & Diagnosis
Rajiv Singh, OMICS J Radiol 2016, 6:5(Suppl)
Medical image fusion: applications, approaches and evaluation
Rajiv Singh
Banasthali University, India
Medical image processing is a rapidly growing area of research for the last three decades. X-ray, ultrasound, MRI (magnetic
resonance imaging) and CT (computed tomography) are a few examples of medical imaging sensors which are used
for extracting clinical information. These sensors provide complementary information about patient’s pathology, anatomy,
and physiology. For example, CT is widely used for tumor and anatomical detection, whereas information about soft tissues
is obtained by MRI. Similarly, other medical imaging techniques like fMRI (functional magnetic resonance imaging), PET
(positron emission tomography), SPECT (single positron emission computed tomography) provide functional and metabolic
information. Further, T1-MRI image provides details about anatomical structure of tissues, whereas T2-MRI image gives
information about normal and abnormal tissues. Hence, one can easily conclude that none of these modalities is able to carry
all relevant information in a single image. Therefore, multimodal medical image fusion is required to obtain all possible relevant
information in a single composite image for better diagnosis and treatment. Spatial and transform domain approaches have
been widely used for medical image fusion. These techniques include PCA (principal component analysis), linear fusion etc.,
and multiresolution fusion scheme using wavelet and pyramid transforms. Subjective and objective evaluations are the two
possible ways to assess fusion algorithms. Subjective evaluation can be performed by medical experts, whereas for objective
evaluation, reference and non reference metrics have been used. For medical image fusion, non-reference metrics are more
suitable as we do not have any reference medical image for comparison of fused image. However, combined subjective and
objective evaluation of fusion algorithms has been found beneficial for better analysis of fusion results.
Biography
Rajiv Singh is an Assistant Professor at the Department of Computer Science, Banasthali University, Banasthali, Rajasthan, India. His research areas of interest
are medical image processing, computer vision, information fusion and wavelet analysis. He has published several papers in refereed journals and conferences.
He has served as reviewer for reputed journals like Information Fusion, IEEE Transactions on Biomedical Engineering, IEEE Transactions on Image Processing,
IET Image Processing and many conferences. He is a member of IEEE and ACM.