Publications by authors named "Xuanle Li"
Predicting tumor biomarkers with high precision is essential for improving the diagnostic accuracy and developing more effective treatment strategies. This paper proposes a machine learning model that utilizes CT images and biopsy whole slide images (WSI) to classify mesothelin expression levels in pancreatic cancer. By combining multimodal learning and stochastic configuration networks, a radiopathomics mesothelin-prediction system named RPMSNet is developed.
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- Contrast agent injections enhance the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in T2-weighted fat-suppressed (T2 FS) MRI sequences, improving image quality for diagnosing breast tumors.
- While there was some fluctuation in apparent diffusion coefficient (ADC) values in diffusion-weighted imaging (DWI) after contrast injections, it did not significantly affect their effectiveness in distinguishing between benign and malignant tumors.
- The study concluded that while contrast agents improve image quality in T2 FS imaging, they do not substantially change the ability to identify different types of breast tumors based on ADC values.