Medical image segmentation is one of the most important tasks in modern healthcare. Every pixel in a scan tells a story, whether it marks a healthy cell, a cancerous growth, or a vital organ boundary.

Lipids are difficult to detect with light microscopy. Using a new chemical labeling strategy, a Dresden-based team led by ...

Dresden research team develops novel imaging approach to visualize individual lipids in cells and uncovers the main transport mechanism for lipids within the cell. Dr. André Nadler Email: ...

How overcommitment derails projects, and what managers can do instead. Mark Mortensen, a professor of organizational behavior at INSEAD, discusses the research on “multiteaming”—when employees work ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs.

Accurate and generalizable segmentation of medical images remains a challenging task due to boundary ambiguity and variations across domains. In this paper, an implicit transformer framework with a ...

1 College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China 2 Institute for Complexity Science, Henan University of Technology, Zhengzhou, China Tongue is ...

The dataset PanNuke-Mini-ImageMask-Dataset-With-Categorize-Masks.zip. used here has been taken from.

Abstract: In recent times, leveraging lesion text as supplementary data to enhance the performance of medical image segmentation models has garnered attention. Previous approaches only used attention ...