PanNuke: An Open Pan-Cancer Histology Dataset for Nuclei Instance Segmentation and Classification

By Jevgenij Gamper, Navid Alemi Koohbanani, Ksenija Benet, A. Khuram, Nasir M. Rajpoot. European Congress on Digital Pathology, 2019

310 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/b218b13756f3aacadf5f06d09652058d024dc9d4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Colin P. Elkin
2. V. Devabhaktuni
3. Sidike Paheding
4. Nahian Alam Siddique

In Computer Vision and Pattern Recognition

1. Colin P. Elkin
2. V. Devabhaktuni
3. Sidike Paheding
4. Nahian Alam Siddique

In Radiology, Nuclear Medicine and Imaging

1. Colin P. Elkin
2. V. Devabhaktuni
3. Sidike Paheding
4. Nahian Alam Siddique

Citations in the corpus

• U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications (2020, background): “Ground truth of samples of different tissues from the PanNuke dataset [285], [286].”