Radiation dose reduction with dictionary learning based processing for head CT.Reportar como inadecuado

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* Corresponding author 1 CRIBS - Centre de Recherche en Information Biomédicale sino-français 2 LIST - Laboratory of Image Science and Technology Nanjing 3 Key Laboratory of Computer Network and Information Integration 4 Key Laboratory of Photoelectronic Imaging Technology and System 5 Department of Radiology 6 LTSI - Laboratoire Traitement du Signal et de l-Image

Abstract : : In CT, ionizing radiation exposure from the scan has attracted much concern from patients and doctors. This work is aimed at improving head CT images from low-dose scans by using a fast Dictionary learning DL based post-processing. Both Low-dose CT LDCT and Standard-dose CT SDCT nonenhanced head images were acquired in head examination from a multi-detector row Siemens Somatom Sensation 16 CT scanner. One hundred patients were involved in the experiments. Two groups of LDCT images were acquired with 50 % LDCT50 % and 25 % LDCT25 % tube current setting in SDCT. To give quantitative evaluation, Signal to noise ratio SNR and Contrast to noise ratio CNR were computed from the Hounsfield unit HU measurements of GM, WM and CSF tissues. A blinded qualitative analysis was also performed to assess the processed LDCT datasets. Fifty and seventy five percent dose reductions are obtained for the two LDCT groups LDCT50 %, 1.15 ± 0.1 mSv; LDCT25 %, 0.58 ± 0.1 mSv; SDCT, 2.32 ± 0.1 mSv; P 

Autor: Yang Chen - Luyao Shi - Jiang Yang - Yining Hu - Limin Luo - Xindao Yin - Jean-Louis Coatrieux -

Fuente: https://hal.archives-ouvertes.fr/


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