cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.647685.v1
title: CIL:28765

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 0.30 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.647686.v1
title: CIL:28766

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 0.30 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.647681
title: CIL:28761

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 0.30 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.647682
title: CIL:28762

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 0.30 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.647683.v1
title: CIL:28763

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 0.30 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.647680
title: CIL:28760

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 0.30 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.647681.v1
title: CIL:28761

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 0.30 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.647682.v1
title: CIL:28762

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 0.30 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.647677
title: CIL:28757

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 0.30 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.647678
title: CIL:28758

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 0.30 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.647679
title: CIL:28759

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 0.30 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.647680.v1
title: CIL:28760

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 0.30 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.647676
title: CIL:28756

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 0.30 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.647677.v1
title: CIL:28757

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 0.30 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.647678.v1
title: CIL:28758

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 0.30 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.647679.v1
title: CIL:28759

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 0.30 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.647673
title: CIL:28754

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 0.30 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.647675
title: CIL:28755

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 0.30 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.647676.v1
title: CIL:28756

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 0.30 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.647672
title: CIL:28753

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).