Name
Abstract | ||
|---|---|---|
A multi-scale (MS) decomposition method for contrast enhancement of Micro Dose (MD) X-ray images is presented in this paper. First, we get a denoised version of the input exploiting a non-local means filter with adaptable parameters setting that we defined in a former approach. Then, the MS representations of the input and of its de-noised version are combined to obtain an optimal image in terms of preservation of details and noise attenuation. The efficiency of the algorithm is demonstrated by quantitative and qualitative assessments on both phantoms and clinical MD images. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ISBI.2014.6867915 | Biomedical Imaging |
Keywords | DocType | ISSN |
dosimetry,image denoising,medical image processing,phantoms,MD X-ray image contrast enhancement,MS decomposition method,adaptable parameter setting,clinical MD image contrast enhancement,clinical microdose image contrast enhancement,denoised input version,image detail preservation,image noise attenuation,input MS representation,input multiscale representation,microdose X-ray image,multiscale decomposition method,nonlocal means filter,optimal image contrast enhancement,phantom image contrast enhancement,qualitative algorithm efficiency assessment,quantitative algorithm efficiency assessment,Micro Dose X-ray imaging,Multi-scale decomposition,Non-local means filter | Conference | 1945-7928 |
Citations | PageRank | References |
1 | 0.36 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paolo Irrera | 1 | 1 | 0.36 |
| Isabelle Bloch | 2 | 2123 | 170.75 |
| Maurice Delplanque | 3 | 1 | 0.69 |