Ruhai Zou's research while affiliated with Sun Yat-Sen University Cancer Center and other places
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Publications (3)
Ultrasound imaging can vary in style/appearance due to differences in scanning equipment and other factors, resulting in degraded segmentation and classification performance of deep learning models for ultrasound image analysis. Previous studies have attempted to solve this problem by using style transfer and augmentation techniques, but these meth...
Objective:
To develop a deep learning-based method with information fusion of US images and RF signals for better classification of thyroid nodules (TNs).
Methods:
One hundred sixty-three pairs of US images and RF signals of TNs from a cohort of adult patients were used for analysis. We developed an information fusion-based joint convolutional n...
PurposeCervical lymph-node (CLN) metastasis commonly occurs in patients with nasopharyngeal carcinoma (NPC) metastasis. The presence of Epstein–Barr virus (EBV) genomes in neck lymph nodes may diagnose CLN. This research was designed to appraise the diagnostic value of EBV concentration for cervical lymph nodes in NPC.Methods
Two hundred and fifty-...
Citations
... Radiomics has also been used to diagnose cytologically uncertain nodules (49)(50)(51), lymph node metastases (52,53), and extrathyroidal extension (54). Many studies employing AI for evaluating the thyroid are mainly based on 2D-US images (48,55,56). In 2015, LeCun introduced the principles of deep learning and convolutional neural networks (CNNs) (18), attracting the interest of many researchers. ...
... The plasma EBV DNA is mainly derived from tumor cells, appears to correlate closely with the presence of residual tumors. Li et al. (51) proposed that ultrasound-guided cervical lymph node (CLN) FNA detection of EBV concentration may provide a new method with high sensitivity and specificity for the diagnosis of CLN metastasis. However, there are still some controversies, including the effects of sample collection, horizontal cutting, and plasma EBV. ...
