Denoising images rendered from scan data acquired by computed tomography (CT), including receiving CT scan data and generating a grid of pixels, for a first pixel channel, based at least in part on the CT scan data, each pixel having an associated radiance value. Methods include iteratively tracing a plurality of rays originating at a camera position based at least in part on radiance values of intersected pixels to produce a Monte Carlo estimate image and applying a denoising algorithm to the Monte Carlo estimate image to produce a denoised image. Methods further include determining one or more weights based at least in part on the Monte Carlo estimate image and the denoised image. Methods further include blending the Monte Carlo estimate image and the denoised image based at least in part on said one or more weights to produce a rendered image.
SYSTEMS AND METHODS FOR DENOISING IMAGES RENDERED FROM SCAN DATA ACQUIREDBY COMPUTED TOMOGRAPHY / Elena Denisova,Leonardo Bocchi. - (2024).
SYSTEMS AND METHODS FOR DENOISING IMAGES RENDERED FROM SCAN DATA ACQUIREDBY COMPUTED TOMOGRAPHY
Elena Denisova
Conceptualization
;Leonardo BocchiSupervision
2024
Abstract
Denoising images rendered from scan data acquired by computed tomography (CT), including receiving CT scan data and generating a grid of pixels, for a first pixel channel, based at least in part on the CT scan data, each pixel having an associated radiance value. Methods include iteratively tracing a plurality of rays originating at a camera position based at least in part on radiance values of intersected pixels to produce a Monte Carlo estimate image and applying a denoising algorithm to the Monte Carlo estimate image to produce a denoised image. Methods further include determining one or more weights based at least in part on the Monte Carlo estimate image and the denoised image. Methods further include blending the Monte Carlo estimate image and the denoised image based at least in part on said one or more weights to produce a rendered image.File | Dimensione | Formato | |
---|---|---|---|
20792.P1065 Application.pdf
Accesso chiuso
Tipologia:
Pdf editoriale (Version of record)
Licenza:
Tutti i diritti riservati
Dimensione
672.44 kB
Formato
Adobe PDF
|
672.44 kB | Adobe PDF | Richiedi una copia |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.