… To the best of our knowledge, multi-modality fusion radiomics features from different levels
have not been comprehensively investigated and compared in prognostic tasks. Thus, in the …

… PET, and 10 image-level fused datasets. The best OS performance was … Our study
demonstrates that our multi-modality fusion … when combining multi modality fusion techniques with …

… automatic co-registration, result in more accurate multi-modality models. To obviate the
inaccuracy, introduced by multi-modality data fusion, a 3D resection planning based solely on …

… [Citation18] showed that late ensemble of CT-, PET-only (Dice 0.6) performed better than
input-level fusion of CT-PET (Dice 0.58). Our results reiterate the improvement of late fusion …

… Based on the results on independent test group, our proposed multi-modality Dense-Net (…
multi-modality Dense-Net can enable satisfied GTV segmentation for HNC using multi-modality …

… Segmentation of head and neck cancer (HNC) primary tumors on medical images is an
essential, yet labor-intensive, aspect of radiotherapy. PET/CT imaging offers a unique ability to …

… the single-modality and late fusion multi-modality strategy for CT-PET and CT-MRI study
on the training set and test set, respectively. Multi-modality CT + PET image information …

… Additionally, we designed a multi-modality convolutional neural network … multi-modality
fusion radiomics: application to PET and CT imaging for prognostication of head and neck cancer …

… It is used efficiently for brain diagnosis, detection [7] of lung cancer, detection of head and
neck cancer, fusion of multimodalities, etc. The image quality in SPECT is poor and is …

… -level fusion multi-modality radiomics models outperformed single-modality, feature-level
fusion, … heterogeneity characterization in head and neck cancer. The best results were obtained …