We present a cross-modality generation framework that learns to generate translated modalities from given modalities in MR images. Our proposed method performs Image Modality Translation (abbreviated as IMT) by means of a deep learning model that leverag
We develop a novel cross-modality generation framework that learns to generate predicted modalities from given modalities in MR images without real acquisition. Our proposed method performs image-to-image translation by means of a deep learning model that levera...
Recently, cross-domain medical image-to-image (I2I) translation based on deep learning has gained prominence, which is expected to effectively resolve these issues (Armanious et al., 2020, Dar et al., 2019, Liu et al., 2021, Zhou et al., 2020). Cross-domain I2I translation refers to ...
Herewith, we introduce PASTA, a novel pathology-aware image translation framework based on conditional diffusion models. Compared to the state-of-the-art methods, PASTAexcels in preserving both structural and pathological details in the target modality, which is achieved through its highly interactive...
Full size image Study characteristics Tables1and2present a description of the included cross-sectional and prospective studies, respectively. Fig. S3 describes the regional distribution of the included cross-sectional and longitudinal studies. Fig. S4 describes the MeDi assessment cut-off score of the...
and thus facilitating this cross-modality integration is vital for mitigating limitations of each individual objective assessment approach23,24. We augment the analysis of overall BOLD responses with a parallel study of the expression in this data of Neurosynth-derived templates25and adult pain signature...
Image-guided radiotherapies (IGRTs), particularly those permitting soft-tissue visualisation, such as cone-beam CT (CBCT), prior to treatment delivery, have already demonstrated step-wise improvement in target coverage. This has been achieved using smaller margins and a subsequent reduction in ...
Magnetic resonance imaging (MRI) has become an essential imaging modality in both staging and targets volume (TV) delineation for head and neck (H&N) cancer radiotherapy (RT) owing to its intrinsically superior soft-tissue contrast, functional information, high resolution and non-radiation [1,2,...
The icomaia solution was developed to exploit inter-hemispheric tissue differences through a process involving image preprocessing, model selection, and training strategy optimization. Regarding image preprocessing, potential misalignments between NCCT and MRI images were rectified through cross-modality registra...
Therefore, we performed the current systematic review and meta-analysis of population-based studies to assess the cross-sectional and longitudinal associations between the MeDi and MRI markers, including TBV, GMV, WMV, WMH, and HCV among elderly adults....