Medical image fusion using combination of PCA and wavelet analysis

Krishn, Abhinav; Bhateja, Vikrant; Himanshi,; Sahu, Akanksha

doi:10.1109/icacci.2014.6968636

Cited by 47 publications

(18 citation statements)

References 37 publications

(31 reference statements)

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“…IV. In this stage, the decomposed approximation and the detailed coefficients from each of the source images are fused by PCA [9], [28]- [29]. PCA being an orthogonal transform helps to reduce the redundancy present in both the source images as well as serves to improve upon the non-directionality limitation of SWT.…”

Section: Proposed Fusion Methodologymentioning

confidence: 99%

Multimodal Medical Image Sensor Fusion Framework Using Cascade of Wavelet and Contourlet Transform Domains

et al. 2015

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Section: Proposed Fusion Methodologymentioning

confidence: 99%

Multimodal Medical Image Sensor Fusion Framework Using Cascade of Wavelet and Contourlet Transform Domains

et al. 2015

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“…Wavelet transform family includes DTCWT [16], SWT [17], Redundant Wavelet Transform [18]. [22]- [24], DWT [19] etc. So far many works had been done in these fields.…”

Section: Introductionmentioning

confidence: 99%

“…V.P.S. Naidu and J. R. Raol [21] employed image fusion using wavelets technique and Principle Component Analysis (PCA) [22]- [24] as the fusion rule. Fused image showed better performance than simple averaging algorithm but wavelet is suitable for one dimensional images therefore high dimensional image cannot be used.…”

Section: Introductionmentioning

confidence: 99%

Medical image fusion with Laplacian Pyramids

Sahu¹,

Bhateja²,

Krishn³

et al. 2014

2014 International Conference on Medical Imaging, M-Health and Emerging Communication Systems (MedCom)

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Fusion of various images aids the rejuvenation of complementary attributes of the images. Similarly, medical image fusion constructs a composite image comprehending significant traits from multimodal source images. Current work exhibits medical image fusion utilizing Laplacian Pyramid (LP) employing DCT. LP decomposes the source medical images as different low pass filtered images, resembling a pyramidal structure. As the pyramidal level of decomposition increases, the quality of the fused image also increases. The proposed technique provides a fused image with better edges and information content from human visual system (HVS) point of view. Qualitative and quantitative analysis of the proposed technique is found to be superior than that of Daubechies complex wavelet transform (DCxWT).

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“…Medical image fusion for merging complementary diagnostic content using PCA and Wavelets was carried out by Krishnet al, [21]. The new fusion approach involved sub-band decomposition using 2D-Discrete Wavelet Transform (DWT) to preserve spectral and spatial information.…”

Section: Related Workmentioning

confidence: 99%

BFO – AIS: A Framework for Medical Image Classification Using Soft Computing Techniques

Chitra¹,

Karthikeyan²

2017

IJSC

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Medical images provide diagnostic evidence/information about anatomical pathology. The growth in database is enormous as medical digital image equipment's like Magnetic Resonance Images (MRI), Computed Tomography (CT), and Positron Emission Tomography CT (PET-CT) are part of clinical work. CT images distinguish various tissues according to gray levels to help medical diagnosis. Ct is more reliable for early tumours and haemorrhages detection as it provides anatomical information to plan radio therapy. Medical information systems goals are to deliver information to right persons at the right time and place to improve care process quality and efficiency. This paper proposes an Artificial Immune System (AIS) classifier and proposed feature selection based on hybrid Bacterial Foraging Optimization (BFO) with Local Search (LS) for medical image classification.

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Medical image fusion using combination of PCA and wavelet analysis

Cited by 47 publications

References 37 publications

Multimodal Medical Image Sensor Fusion Framework Using Cascade of Wavelet and Contourlet Transform Domains

Multimodal Medical Image Sensor Fusion Framework Using Cascade of Wavelet and Contourlet Transform Domains

Medical image fusion with Laplacian Pyramids

BFO – AIS: A Framework for Medical Image Classification Using Soft Computing Techniques

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