Publications by authors named "Hongchao Fu"
Article Synopsis
- The study evaluates the effectiveness of a deep learning algorithm (DELTA) for reconstructing CT images of intracranial aneurysms (IAs) compared to traditional hybrid iterative reconstruction (HIR).
- Results showed that DELTA images had significantly lower noise and higher signal and contrast ratios, leading to better overall image quality ratings by radiologists.
- The findings suggest that DELTA enhances diagnostic confidence, particularly for smaller IAs (≤3 mm), indicating its potential for routine use in craniocervical CT angiography.
Background: The intravoxel incoherent motion (IVIM) method of magnetic resonance imaging (MRI) analysis can provide information regarding many physiological and pathological processes. This study aimed to investigate whether IVIM-derived parameters and the apparent diffusion coefficient (ADC) can act as imaging biomarkers for predicting non-small cell lung cancer (NSCLC) response to anti-tumor therapy and compare their performances.
Methods: This prospective study included 45 patients with NSCLC treated with chemotherapy (29 men and 16 women, mean age 57.
To investigate the utility of the pre-immunotherapy contrast-enhanced CT-based texture classification in predicting response to non-small cell lung cancer (NSCLC) immunotherapy treatment. Sixty-three patients with 72 lesions who received immunotherapy were enrolled in this study. We extracted textures including histogram, absolute gradient, run-length matrix, gray-level co-occurrence matrix, autoregressive model, and wavelet transform from pre-immunotherapy contrast-enhanced CT by using Mazda software.
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