Real Tumor

Real tumor research focuses on accurately identifying, segmenting, and characterizing tumors within medical images, primarily to improve diagnosis, treatment planning, and monitoring. Current research employs various deep learning architectures, including U-Net variations, transformers, and convolutional LSTM networks, often incorporating techniques like radiomics and feature disentanglement to enhance performance and interpretability. These advancements aim to improve the speed and accuracy of tumor detection and analysis, ultimately leading to more effective and personalized cancer care.