Online ISSN: 2515-8260

Keywords : Restoration


Modified Solutions Based On Calcium Sulfate For Architectural Monuments Of Bukhara

Vaxitov M.M.; TulaganovA .A; Tojiev I.I.

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 7, Pages 989-999

In the article, based on the results of the physicochemical analysis of the mortar of the brick masonry of the Ismoil Samaniy and Minaret Kalyan mausoleum, it is shown that these mortars are gypsum-lime mortars with organic and mineral addition. Taking this circumstance into account, as a result of further research, modified solutions were obtained for the restoration of the aforementioned architectural monuments.

Denoising And Inpainting Techniques forRestoration of Images

L Praveen Kumar, Akku Madhusudan, Anil Kumar Gona

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 3, Pages 899-906

Digitalinpaintingisthetechniqueoffillinginthemissingregionsofanimageusinginformationfro
mthesurroundingareainavisuallyindistinguishableway.Inthispaper,wetrytoimprovetheExem
plarbasedmethod[2]bymanipulating the values of various parameters like patch size,shape
and size of the mask. We present an analysis of the
impactofvariousgeometricparametersonthequalityofinpaintedimages.Imagedenoisingrefers
totheremovalofunwantednoisefromtheimages.Inmostcases,theimageswhichneedto be
inpainted are noisy, which makes it necessary to
eliminatenoiseandfillinthemissingregionsfromneighboringpixels.Therefore,fillinginofmissi
ngregionsandremovalofnoisearethetwoveryimportanttopicsinimageprocessing.Thispaperals
oaddressestheissueofperformingbothinpaintinganddenoisingsimultaneouslyusingtwodiffer
entapproaches:pipelinedapproachandinterleavedapproach.Theeffectivenessof these
approaches is demonstrated with a number of results onvariousimages.

Image denoising Using Magnetic Resonance Guided Positron Emission Tomography

L Praveen Kumar, Akku Madhusudan, Anil Kumar Gona

European Journal of Molecular & Clinical Medicine, 2019, Volume 6, Issue 1, Pages 239-244

With the growing interest in conducting multi- centre and multi-modality studies on
neurological disorders, post-reconstruction PET image enhancement methods that take advantage
of available anatomical information are becoming more important. In this work, a novel method
for denoising PET images using the subject’s registered T1-weighted MR image is proposed. The
proposed method combines the non-local means approach with the twicing strategy from the image
denoising literature to restore a reconstructed PET image. Preliminary analysis shows promising
improvements in peak signal to noise ratio (PSNR) and contrast recovery coefficients (CRC) of the
lesions when denoising simulated images reconstructed using the MLEM algorithm.