Cc-by-3.0 (5)#
3D HL60 Cell line (synthetic data)#
David Svoboda, Michal Kozubkek, Stanislav Stejskal
Published 2009-06-01
Licensed CC-BY-3.0
One of the principal challenges in counting or segmenting nuclei is dealing with clustered nuclei. To help assess algorithms performance in this regard, this synthetic image set consists of four subsets with increasing degree of clustering. Each subset is also provided in two diferent levels of quality: high SNR and low SNR.
Tags: Ai-Ready
Content type: Data
Assessment of Residual Breast Cancer Cellularity after Neoadjuvant Chemotherapy using Digital Pathology#
Mohammad Peikari, Sherine Salama, Sharon Nofech-Mozes, Anne L. Martel
Published 2017-10-04
Licensed CC-BY-3.0
Breast cancer (BC) is the second most commonly diagnosed cancer in the U.S. with more than 250,000 new cases of invasive breast cancers reported in 2017. The majority of women with locally advanced and a subset of patients with operable breast cancer will undergo systemic therapy prior to their surgery (neoadjuvant therapy/ NAT) to reduce the size of tumor(s) and possibly further undergo breast conserving surgery. The Post-NAT-BRCA dataset is a collection of representative sections from breast resections in patients with residual invasive BC following NAT. Histologic sections were prepared and digitized to produce high resolution, microscopic images of treated BC tumors. Also included, are clinical features and expert pathology annotations of tumor cellularity and cell types. The Residual Cancer Burden Index (RCBi), is a clinically validated tool for assessment of response to NAT associated with prognosis. Tumor cellularity is one of the parameters used for calculating the RCBi. In this dataset, tumor cellularity refers to a measure of residual disease after NAT, in the form of proportion of malignant tumor inside the tumor bed region; also annotated. (See MD Anderson RCB Calculator for a detailed description of tumor cellularity.) Malignant, healthy, lymphocyte and other labels were also provided for individual cells to aid development of cell segmentation algorithms.
Tags: Ai-Ready
Content type: Data
https://www.cancerimagingarchive.net/collection/post-nat-brca/
Chinese Hamster Ovary Cells#
Krisztian Koos, József Molnár, Lóránd Kelemen, Gábor Tamás, Peter Horvath
Published 2016-07-29
Licensed CC-BY-3.0
The image set consists of 60 Differential Interference Contrast (DIC) images of Chinese Hamster Ovary (CHO) cells. The images are taken on an Olympus Cell-R microscope with a 20x lens at the time when the cell initiated their attachment to the bottom of the dish.
Tags: Ai-Ready
Content type: Data
Human Hepatocyte and Murine Fibroblast cells Co-culture experiment#
David J. Logan, Jing Shan, Sangeeta N. Bhatia, Anne E. Carpenter
Published 2016-03-01
Licensed CC-BY-3.0
This 384-well plate has images of co-cultured hepatocytes and fibroblasts. Every other well is populated (A01, A03, …, C01, C03, …) such that 96 wells comprise the data. Each well has 9 sites and thus 9 images associated, totaling 864 images.
Tags: Ai-Ready
Content type: Data
Synthetic images and segmentation masks simulating HL-60 cell nucleus in 3D#
David Svoboda, Michal Kozubek, Stanislav Stejskal, Teresa Zulueta-Coarasa
Published 2024-11-26
Licensed CC-BY-3.0
One of the principal challenges in counting or segmenting nuclei is dealing with clustered nuclei. To help assess algorithms performance in this regard, this synthetic image set consists of four subsets with increasing degree of clustering. Each subset is also provided in two different levels of quality: high SNR and low SNR.
Tags: Ai-Ready
Content type: Data
https://www.ebi.ac.uk/bioimage-archive/galleries/ai/analysed-dataset/S-BIAD1492/