Publications by authors named "Mengde Ling"
Article Synopsis
- - 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.
Background: Osteosarcoma, the most common primary bone tumor originating from osteoblasts, poses a significant challenge in medical practice, particularly among adolescents. Conventional diagnostic methods heavily rely on manual analysis of magnetic resonance imaging (MRI) scans, which often fall short in providing accurate and timely diagnosis. This underscores the critical need for advancements in medical imaging technologies to improve the detection and characterization of osteosarcoma.
View Article and Find Full Text PDF