Merge pull request #771 from NFDI4BIOIMAGE/haesleinhuepf-patch-6

removed duplicate

Author: haesleinhuepf

resources/nfdi4bioimage.yml

@@ -12955,114 +12955,6 @@ resources:
   - https://zenodo.org/records/8252039
   - https://doi.org/10.5281/zenodo.8252039
 
-- authors:
-  - Luke Sorensen
-  - Ayame Saito
-  - Sabrina Poon
-  - Myat Noe Han
-  - Adam Humenick
-  - Peter Neckel
-  - Keith Mutunduwe
-  - Christie Glennan
-  - Narges Mahdavian
-  - Simon JH Brookes
-  - Rachel M McQuade
-  - Jaime PP Foong
-  - Sebastian K. King
-  - "Estibaliz  G\xF3mez-de-Mariscal"
-  - "Arrate Mu\xF1oz-Barrutia"
-  - Robert Haase
-  - Simona Carbone
-  - Nicholas A. Veldhuis
-  - Daniel P. Poole
-  - Pradeep Rajasekhar
-  description: "This upload is associated with the software, Gut Analysis Toolbox (GAT).\n\
-    If you use it please cite:\nSorensen et al. Gut Analysis Toolbox: Automating\
-    \ quantitative analysis of enteric neurons. J Cell Sci 2024; jcs.261950.\
-    \ doi: https://doi.org/10.1242/jcs.261950\nThe upload contains StarDist models\
-    \ for segmenting enteric neurons in 2D, enteric neuronal subtypes in 2D and FPN+ResNet101\
-    \ model for enteric ganglia in 2D in gut wholemount tissue. GAT is implemented in\
-    \ Fiji, but the models can be used in any software that supports StarDist and the\
-    \ use of 2D UNet models. The files here also consist of Python notebooks\
-    \ (Google Colab), training and test data as well as reports on model performance.\n\
-    Note: The enteric ganglia model is has been updated to v3 which uses pytorch and\
-    \ is a different architecture (FPN+ResNet101).\nThe model files are located in the\
-    \ respective folders as zip files. The folders have also been zipped:\n\nNeuron\
-    \ (Hu; StarDist model):\n\nMain folder: 2D_enteric_neuron_model_QA.zip\nStarDist\
-    \ Model File:2D_enteric_neuron_v4_1.zip \nDeepImageJ compatible model: 2D_enteric_neuron.bioimage.io.model.zip\
-    \ (used currently in GAT)\n\n\nNeuronal subtype (StarDist model): \n\n\
-    Main folder: 2D_enteric_neuron_subtype_model_QA.zip\nModel File: 2D_enteric_neuron_subtype_v4.zip\n\
-    DeepImageJ compatible model: 2D_enteric_neuron_subtype.bioimage.io.model.zip (used\
-    \ currently in GAT)\n\n\nEnteric ganglia (2D FPN_ResNet101; Use in FIJI with deepImageJ)\n\
-    \nMain folder: 2D_enteric_ganglia_v3_training.zip\nModel File: 2D_Ganglia_RGB_v3.bioimage.io.model.zip\
-    \ (used currently in GAT)\n\n\n\nFor the all models, files included are:\n\nModel\
-    \ for segmenting cells or ganglia in 2D FIJI. StarDist or 2D UNet.\nTraining and\
-    \ Test datasets used for training.\nGoogle Colab notebooks used for training and\
-    \ quality assurance (ZeroCost DL4Mic notebooks).\nPython notebook and code for training\
-    \ ganglia model with QA.\nQuality assurance reports generated from above notebooks.\n\
-    StarDist model exported for use in QuPath.\n\nThe model files can be used within\
-    \ can be used within the software, StarDist. They are intended to be used\
-    \ within FIJI or QuPath, but can be used in any software that supports the implementation\
-    \ of StarDist in 2D.\nData:\nAll the images were collected from 4 different research\
-    \ labs and a public database (SPARC database) to account for variations in image\
-    \ acquisition, sample preparation and immunolabelling.\nFor enteric neurons the\
-    \ pan-neuronal marker, Hu has been used and the  2D wholemounts images\
-    \ from mouse, rat and human tissue.\nFor enteric neuronal subtypes, 2D images for\
-    \ nNOS, MOR, DOR, ChAT, Calretinin, Calbindin, Neurofilament, CGRP and SST from\
-    \ mouse tissue have been used..\n25 images were used from the following entries\
-    \ in the SPARC database:\n\nHoward, M. (2021). 3D imaging of enteric neurons\
-    \ in mouse (Version 1) [Data set]. SPARC Consortium. \nGraham, K. D., Huerta-Lopez,\
-    \ S., Sengupta, R., Shenoy, A., Schneider, S., Wright, C. M., Feldman, M., Furth,\
-    \ E., Lemke, A., Wilkins, B. J., Naji, A., Doolin, E., Howard, M., & Heuckeroth,\
-    \ R. (2020). Robust 3-Dimensional visualization of human colon enteric nervous system\
-    \ without tissue sectioning (Version 1) [Data set]. SPARC Consortium.\nWang, L.,\
-    \ Yuan, P.-Q., Gould, T. and Tache, Y. (2021). Antibodies Tested in theColon –\
-    \ Mouse (Version 1) [Data set]. SPARC Consortium. doi:10.26275/i7dl-58h\n\nAdditional\
-    \ images for new ganglia model:\n\nHamnett, R., Dershowitz, L. B., Sampathkumar,\
-    \ V., Wang, Z., Gomez-Frittelli, J., De Andrade, V., Kasthuri, N., Druckmann, S.\
-    \ and Kaltschmidt, J. A. (2022b). Regional cytoarchitecture of the adult and developing\
-    \ mouse enteric nervous system. Curr. Biol. 32, 4483-4492.e5.\n\nThe images have\
-    \ been acquired using a combination different microscopes. The images for the mouse\
-    \ tissue were acquired using: \n\n\nLeica TCS-SP8 confocal system (20x HC PL\
-    \ APO NA 1.33, 40 x HC PL APO NA 1.3) \n\n\nLeica TCS-SP8 lightning confocal\
-    \ system (20x HC PL APO NA 0.88) \n\n\nZeiss Axio Imager M2 (20X HC PL APO\
-    \ NA 0.3) \n\n\nZeiss Axio Imager Z1 (10X HC PL APO NA 0.45) \n\n\nHuman\
-    \ tissue images were acquired using: \n\n\nIX71 Olympus microscope (10X HC\
-    \ PL APO NA 0.3) \n\n\nFor more information, visit the Documentation website.\n\
-    NOTE: The images for enteric neurons and neuronal subtypes have been rescaled to\
-    \ 0.568 µm/pixel for mouse and rat. For human neurons, it has been rescaled\
-    \ to 0.9 µm/pixel . This is to ensure the neuronal cell bodies have similar\
-    \ pixel area across images. The area of cells in pixels can vary based on resolution\
-    \ of image, magnification of objective used, animal species (larger animals ->\
-    \ larger neurons) and potentially how the tissue is stretched during wholemount\
-    \ preparation \nAverage neuron area for neuronal model: 701.2 ±\
-    \ 195.9 pixel2 (Mean ± SD, 6267 cells)\nAverage neuron area for neuronal\
-    \ subtype model: 880.9 ± 316 pixel2 (Mean ± SD, 924 cells)\n\
-    Software References:\nStardist\nSchmidt, U., Weigert, M., Broaddus, C., & Myers,\
-    \ G. (2018, September). Cell detection with star-convex polygons. In International\
-    \ Conference on Medical Image Computing and Computer-Assisted Intervention (pp.\
-    \ 265-273). Springer, Cham.\ndeepImageJ\nGómez-de-Mariscal, E., García-López-de-Haro,\
-    \ C., Ouyang, W., Donati, L., Lundberg, E., Unser, M., Muñoz-Barrutia, A.\
-    \ and Sage, D., 2021. DeepImageJ: A user-friendly environment to run deep learning\
-    \ models in ImageJ. Nature Methods, 18(10), pp.1192-1195.\nZeroCost DL4Mic\n\
-    von Chamier, L., Laine, R.F., Jukkala, J., Spahn, C., Krentzel, D., Nehme, E., Lerche,\
-    \ M., Hernández-Pérez, S., Mattila, P.K., Karinou, E. and Holden,\
-    \ S., 2021. Democratising deep learning for microscopy with ZeroCostDL4Mic. Nature\
-    \ communications, 12(1), pp.1-18."
-  license: cc-by-4.0
-  name: 'Gut Analysis Toolbox: Training data and 2D models for segmenting enteric neurons,
-    neuronal subtypes and ganglia'
-  num_downloads: 695
-  publication_date: '2025-05-01'
-  submission_date: '2025-05-29T19:38:39.675784'
-  tags:
-  - AI-ready
-  type:
-  - Data
-  url:
-  - https://zenodo.org/records/15314214
-  - https://doi.org/10.5281/zenodo.15314214
-  
 - authors:
   - Johanna Jukkala
   - Guillaume Jacquemet