cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.647662
title: CIL:28743

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647663.v1
title: CIL:28744

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647661
title: CIL:28742

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647659
title: CIL:28740

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647660
title: CIL:28741

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647662.v1
title: CIL:28743

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647659.v1
title: CIL:28740

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647660.v1
title: CIL:28741

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647661.v1
title: CIL:28742

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647656
title: CIL:28737

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647658
title: CIL:28739

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647657
title: CIL:28738

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647658.v1
title: CIL:28739

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647654
title: CIL:28735

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647655
title: CIL:28736

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647656.v1
title: CIL:28737

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647657.v1
title: CIL:28738

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647654.v1
title: CIL:28735

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647655.v1
title: CIL:28736

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.45 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).
DOI: 10.6084/m9.figshare.647650
title: CIL:28731

description: 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 five subsets with increasing degree of clustering. Five subsets of 20 images each are provided. Each image contains 300 objects, but the objects overlap and cluster with overlap probability ranging from 0.0 to 0.6, and can be found with CIL 27833, 27853, 28754, 28734, and 28714, respectively. This image set has 0.60 probability overlap. The images were generated with the SIMCEP (http://www.cs.tut.fi/sgn/csb/simcep/tool.html) simulating platform for fluorescent cell population images (Lehmussola et al., IEEE T. Med. Imaging, 2007 and Lehmussola et al., P. IEEE, 2008). Ground truth for foreground/background segmentation are available as binary images as the second image in the tiff image stack. Recommended citation We used the Synthetic 1 image set (Ruusuvuori et al., in Proc. of the 16th European Signal Processing Conference (EUSIPCO-2008), 2008), available from the Broad Bioimage Benchmark Collection (www.broad.mit.edu/bbbc).