Publications by authors named "Bijiao Ding"
Objective: Segmenting and reconstructing 3D models of bone tumors from 2D image data is of great significance for assisting disease diagnosis and treatment. However, due to the low distinguishability of tumors and surrounding tissues in images, existing methods lack accuracy and stability. This study proposes a U-Net model based on double dimensionality reduction and channel attention gating mechanism, namely the DCU-Net model for oncological image segmentation.
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- - The study addresses challenges in retrieving microscopic images of osteosarcoma by using advanced deep hashing techniques and attention mechanisms, which enhance both efficiency and accuracy in image retrieval.
- - The algorithm employs various preprocessing methods and a WRN-AM model for feature extraction, achieving a high classification accuracy of 93.2% and a mean Average Precision (mAP) of 97.09% with 64-bit hash codes.
- - This innovative method not only improves the retrieval process for healthcare professionals, aiding in faster diagnosis and treatment planning, but also benefits researchers by enhancing the utilization of medical image data for further advancements in the field.
Unlabelled: This study aims to predict bone metastasis in lung cancer patients using radiomics and deep learning. Early prediction of bone metastasis is crucial for timely intervention and personalized treatment plans. This can improve patient outcomes and quality of life.
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