Introduction: Liver cancer is among the deadliest malignancies worldwide, and both its incidence and mortality continue to rise. Precise tumor segmentation often remains difficult due to heterogeneous ...

Abstract: Accurate segmentation of brain tumor from multimodality MRI is an important task for the diagnosis, treatment decision and survival estimation of neuro-oncology. In this paper, a unified ...

1 Anhui University of Chinese Medicine, Hefei, China 2 College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China Medical image segmentation is fundamental ...

Tumor segmentation in lung CT using U-Net, U-Net++ and an augmentation-enhanced U-Net. Best validation Dice: 0.807 (MSD lung dataset).

Abstract: The proposed work focuses on using LadderNet for Brain Tumor segmentation using MRI signals through the dataset as an input. The method is helpful in computerized medical analysis. Although ...

1 Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA. 2 Department of Mathematics and Computer Science, Islamic Azad University, Science and Research Branch, Tehran, ...

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...

The Trump administration’s move sets back a decades-long effort to end the use of the material, which is widely banned in other countries. By Hiroko Tabuchi The Trump administration plans to ...

Use of an artificial intelligence model to predict Ki67 from H&E-stained whole slides images in breast cancer. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does ...