Bo Liu

Defining Radiation Target Volumes with AI-Driven Predictions of Glioma Recurrence from MRSI, Diffusion MRI, and Transformers

Harshita Kukreja, Nate Tran, Bo Liu, Jacob Ellison et autres

Motivation: Presurgery MR scans have a higher percentage of tumor voxels and can be used as a better signal to predict tumor progression using AI-driven models. Goal(s): We show deep learning can be used to predict tumor progression in patients diagnosed with …

Association between single and multiple dietary vitamin exposure and heart failure risk: a cross-sectional study

Jiashun Huang, Feifei Zhong, Bo Liu, Xi Chen et autres

Background: Heart failure (HF) is a prevalent cardiovascular disease exhibiting a complex interplay with dietary vitamin intake. This study employed a comprehensive methodology to investigate the association between exposure to single and multiple dietary vitamins and the risk of HF, with the …

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Multiparametric analysis of early treatment changes in glioma after receiving radiation therapy

Yan Li, Adam W. Autry, Zhongjie Wang, Sana Vaziri et autres

Motivation: Understanding how MR imaging markers change in normal appearing brain tissue over the course of RT for different dose distributions could help shed light on which parts of the brain are more susceptible to RT. Goal(s): To examine early changes in …

Defining radiation target volumes for glioblastoma from predictions of tumor recurrence with AI and diffusion & metabolic MRI

Nate Tran, Jacob Ellison, Tracy L. Luks, Yan Li et autres

Using pre-radiotherapy anatomical, diffusion, and metabolic MRI from 42 patients newly-diagnosed with GBM, we first used Random Forest models to identify voxels that later exhibit either contrast-enhancing or T2 lesion progression. We then applied convolutional encoder-decoder neural networks to pre-radiotherapy imaging to …

Application of Machine Learning Optimization in Cloud Computing Resource Scheduling and Management

Y.W. Zhang, Bo Liu, Yulu Gong, Jiaxin Huang et autres

In recent years, cloud computing has been widely used. Cloud computing refers to the centralized computing resources, users through the access to the centralized resources to complete the calculation, the cloud computing center will return the results of the program processing to …

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Detection of Esophageal Cancer Lesions Based on CBAM Faster R-CNN

Bo Liu, Xinyu Zhao, Hao Hu, Qunwei Lin et autres

Esophageal cancer is a common malignant tumor in daily life, which seriously affects human health. Esophageal cancer in China. The incidence rate is among the highest in the world, and there are a large number of new cases of esophageal cancer every …

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RADT-26. IMPROVING RADIATION TARGET VOLUME DEFINITION FOR GLIOBLASTOMA USING PREDICTIONS OF TUMOR RECURRENCE FROM MACHINE LEARNING AND PRE-RADIOTHERAPY ADVANCED MRI

Nate Tran, Tracy L. Luks, Jacob Ellison, Devika Nair et autres

Abstract INTRODUCTION Standard-of-care (SOC) radiation therapy (RT) planning only utilizes a fairly 1.5-2cm uniform expansion of T2-weighted-FLAIR MRI lesion to generate a clinical target volume (2cm-CTV), without considering the spatial heterogeneity and infiltrative nature of glioblastomas. This study aimed to use multi-parametric …

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A multi-view co-training network for semi-supervised medical image-based prognostic prediction

Hailin Li, Siwen Wang, Bo Liu, Mengjie Fang et autres

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Identification and diagnosis of mammographic malignant architectural distortion using a deep learning based mask regional convolutional neural network

Yuanyuan Liu, Yunfei Tong, Yun Wan, Ziqiang Xia et autres

Background: Architectural distortion (AD) is a common imaging manifestation of breast cancer, but is also seen in benign lesions. This study aimed to construct deep learning models using mask regional convolutional neural network (Mask-RCNN) for AD identification in full-field digital mammography (FFDM) …

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DCT-Net: An effective method to diagnose retinal tears from B-scan ultrasound images

Ke Li, Qiaolin Zhu, Jian‐Zhang Wu, Juntao Ding et autres

Retinal tears (RTs) are usually detected by B-scan ultrasound images, particularly for individuals with complex eye conditions. However, traditional manual techniques for reading ultrasound images have the potential to overlook or inaccurately diagnose conditions. Thus, the development of rapid and accurate approaches …

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The predictive potential of contrast-enhanced computed tomography based radiomics in the preoperative staging of cT4 gastric cancer

Bo Liu, Dengyun Zhang, He Wang, Hexiang Wang et autres

Background: The accuracy of preoperative staging is crucial for cT4 stage gastric cancer patients. The aim of this study was to develop the radiomics model and evaluate its predictive potential for differentiating preoperative cT4 stage gastric cancer patients into pT4b and no-pT4b …

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Atlas of Currently-Available Human MAbs and Escape to Newly-Emerging Omicron BA.1/BA.1.1/BA.2/BA.3

Min Mei Huang, Lili Wu, Anqi Zheng, Yufeng Xie et autres

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