Details

Autor(en) / Beteiligte

• Lin, Hongxiang
• Figini, Matteo
• D’Arco, Felice
• Ogbole, Godwin
• Tanno, Ryutaro
• Blumberg, Stefano B.
• Ronan, Lisa
• Brown, Biobele J.
• Carmichael, David W.
• Lagunju, Ikeoluwa
• Cross, Judith Helen
• Fernandez-Reyes, Delmiro
• Alexander, Daniel C.

Titel

Low-field magnetic resonance image enhancement via stochastic image quality transfer

Ist Teil von

• Medical image analysis, 2023-07, Vol.87, p.102807-102807, Article 102807

Ort / Verlag

Netherlands: Elsevier B.V

Erscheinungsjahr

2023

Quelle

MEDLINE

Beschreibungen/Notizen

• Low-field (<1T) magnetic resonance imaging (MRI) scanners remain in widespread use in low- and middle-income countries (LMICs) and are commonly used for some applications in higher income countries e.g. for small child patients with obesity, claustrophobia, implants, or tattoos. However, low-field MR images commonly have lower resolution and poorer contrast than images from high field (1.5T, 3T, and above). Here, we present Image Quality Transfer (IQT) to enhance low-field structural MRI by estimating from a low-field image the image we would have obtained from the same subject at high field. Our approach uses (i) a stochastic low-field image simulator as the forward model to capture uncertainty and variation in the contrast of low-field images corresponding to a particular high-field image, and (ii) an anisotropic U-Net variant specifically designed for the IQT inverse problem. We evaluate the proposed algorithm both in simulation and using multi-contrast (T1-weighted, T2-weighted, and fluid attenuated inversion recovery (FLAIR)) clinical low-field MRI data from an LMIC hospital. We show the efficacy of IQT in improving contrast and resolution of low-field MR images. We demonstrate that IQT-enhanced images have potential for enhancing visualisation of anatomical structures and pathological lesions of clinical relevance from the perspective of radiologists. IQT is proved to have capability of boosting the diagnostic value of low-field MRI, especially in low-resource settings. [Display omitted] •IQT boosts low-field MRI by estimating the image having been obtained at high field.•Stochastic decimation simulator is devised to account for low-field MRI variability.•Anisotropic U-Net architecture handles the anisotropic-to-isotropic voxel mapping.•Our results show that IQT can enhance the visualisation of anatomical structures.•IQT potentially aids radiologists in characterising lesions of clinical relevance.