4/14🔬 We captured 16-to 22-hour 3D movies of this process. However, segmenting and tracking individual cells in a dense 3D tissue is a challenging task. We built a deep learning pipeline that combines the forces of #StarDist, #UNET, #Cellpose, and #TrackMate. 💪#ImageAnalysis
September 22, 2025 at 9:37 AM
4/14🔬 We captured 16-to 22-hour 3D movies of this process. However, segmenting and tracking individual cells in a dense 3D tissue is a challenging task. We built a deep learning pipeline that combines the forces of #StarDist, #UNET, #Cellpose, and #TrackMate. 💪#ImageAnalysis
Day 3️⃣ of our @embo.org course on "Advanced methods in bioimage analysis" at @embl.org with "Practical session 3: Tracking" 🔬🦠🔀.
@jytinevez.bsky.social is already shining at the stage! 🕺🪩.
Important update: #TrackMate v8 is coming! 🤗
@jytinevez.bsky.social is already shining at the stage! 🕺🪩.
Important update: #TrackMate v8 is coming! 🤗
September 16, 2025 at 8:10 AM
Day 3️⃣ of our @embo.org course on "Advanced methods in bioimage analysis" at @embl.org with "Practical session 3: Tracking" 🔬🦠🔀.
@jytinevez.bsky.social is already shining at the stage! 🕺🪩.
Important update: #TrackMate v8 is coming! 🤗
@jytinevez.bsky.social is already shining at the stage! 🕺🪩.
Important update: #TrackMate v8 is coming! 🤗
Israel A. Huaman, Fares D. E. Ghorabe, Sofya S. Chumakova, Alexandra A. Pisarenko, Alexey E. Dudaev, Tatiana G. Volova, Galina A. Ryltseva, Sviatlana A. Ulasevich, Eka...
Cellpose+, a morphological analysis tool for feature extraction of stained cell images
https://arxiv.org/abs/2410.18738
Cellpose+, a morphological analysis tool for feature extraction of stained cell images
https://arxiv.org/abs/2410.18738
October 25, 2024 at 8:32 AM
Israel A. Huaman, Fares D. E. Ghorabe, Sofya S. Chumakova, Alexandra A. Pisarenko, Alexey E. Dudaev, Tatiana G. Volova, Galina A. Ryltseva, Sviatlana A. Ulasevich, Eka...
Cellpose+, a morphological analysis tool for feature extraction of stained cell images
https://arxiv.org/abs/2410.18738
Cellpose+, a morphological analysis tool for feature extraction of stained cell images
https://arxiv.org/abs/2410.18738
More details can be found in this discussion. I have a few real images with structure at different scales for which I am going to run cellpose-sam vs cellpose-cyto3 tests on shortly. forum.image.sc/t/cellpose4-...
Cellpose4 (Cellpose-SAM) tests
Below is cellpose3-cyto3 compared to cellpose4-sam on a resolution test image which consists of circles of different sizes. This is based on a test you can find here which shows how to make the spher...
forum.image.sc
May 6, 2025 at 1:15 PM
More details can be found in this discussion. I have a few real images with structure at different scales for which I am going to run cellpose-sam vs cellpose-cyto3 tests on shortly. forum.image.sc/t/cellpose4-...
Shuo Zhao, Jianxu Chen
Data Efficiency and Transfer Robustness in Biomedical Image Segmentation: A Study of Redundancy and Forgetting with Cellpose
https://arxiv.org/abs/2511.04803
Data Efficiency and Transfer Robustness in Biomedical Image Segmentation: A Study of Redundancy and Forgetting with Cellpose
https://arxiv.org/abs/2511.04803
November 10, 2025 at 8:44 AM
Shuo Zhao, Jianxu Chen
Data Efficiency and Transfer Robustness in Biomedical Image Segmentation: A Study of Redundancy and Forgetting with Cellpose
https://arxiv.org/abs/2511.04803
Data Efficiency and Transfer Robustness in Biomedical Image Segmentation: A Study of Redundancy and Forgetting with Cellpose
https://arxiv.org/abs/2511.04803
Qupath + Cellpose + Stardistで細胞質と核をsegmentaionめっちゃ綺麗にできて、細胞ごとにデータ得られる！すごすぎ！
June 15, 2024 at 6:13 AM
Qupath + Cellpose + Stardistで細胞質と核をsegmentaionめっちゃ綺麗にできて、細胞ごとにデータ得られる！すごすぎ！
Ignacio Arganda-Carreras gave us a lecture on the history of Deep Learning in bioimage analysis, stardist cellpose, and how the postprocessing of those outputs are designed.
January 28, 2025 at 7:35 PM
Ignacio Arganda-Carreras gave us a lecture on the history of Deep Learning in bioimage analysis, stardist cellpose, and how the postprocessing of those outputs are designed.
🔬 ML-based segmentation (CellPose, ilastik, QuPath) will replace manual ImageJ counting
Why: reproducibility, throughput, objective quantitation
Lore: Reviewers now expect automated or blinded image analysis
(9/10)
Why: reproducibility, throughput, objective quantitation
Lore: Reviewers now expect automated or blinded image analysis
(9/10)
November 9, 2025 at 4:50 PM
🔬 ML-based segmentation (CellPose, ilastik, QuPath) will replace manual ImageJ counting
Why: reproducibility, throughput, objective quantitation
Lore: Reviewers now expect automated or blinded image analysis
(9/10)
Why: reproducibility, throughput, objective quantitation
Lore: Reviewers now expect automated or blinded image analysis
(9/10)
Difficult to generalize but Cellpose was probably simplest to install even though I ran the remaining two from Google Colab. Low-res images were easier to segment with all 3 tools (cell boundaries are clearly visible). MicroSam surprisingly good even with the confocal but still not reliable.
February 16, 2025 at 9:38 PM
Difficult to generalize but Cellpose was probably simplest to install even though I ran the remaining two from Google Colab. Low-res images were easier to segment with all 3 tools (cell boundaries are clearly visible). MicroSam surprisingly good even with the confocal but still not reliable.
By the way, installation in M1 mac was a bit of a challenge but summarized to the following sequence of installation commands. The problem was with `numba` installation which should happen independently before the cellpose installation.
January 28, 2025 at 7:24 PM
By the way, installation in M1 mac was a bit of a challenge but summarized to the following sequence of installation commands. The problem was with `numba` installation which should happen independently before the cellpose installation.
Absolutely agree. The real challenge isn’t generating probability maps, but separating dense/touching cells. In my experience, postprocessing (Voronoi-Otsu, watershed, etc.) always needs dataset-specific tuning. For standard data, Cellpose seems often faster and just as accurate.
July 18, 2025 at 7:37 AM
Absolutely agree. The real challenge isn’t generating probability maps, but separating dense/touching cells. In my experience, postprocessing (Voronoi-Otsu, watershed, etc.) always needs dataset-specific tuning. For standard data, Cellpose seems often faster and just as accurate.
3D #SpatialMultiomics on the way!😍
Cycle Hybridization Chain Reaction
14 bp split L+R DNA barcodes
3 color channels
Cellpose-based 3D nucleus segmentation
120 RNA probes + 8 antibodies
~50 µm hippocampal slice
44 imaging cycles over 11 days
@science.org 2025
www.science.org/doi/10.1126/...
Cycle Hybridization Chain Reaction
14 bp split L+R DNA barcodes
3 color channels
Cellpose-based 3D nucleus segmentation
120 RNA probes + 8 antibodies
~50 µm hippocampal slice
44 imaging cycles over 11 days
@science.org 2025
www.science.org/doi/10.1126/...
March 20, 2025 at 10:44 AM
3D #SpatialMultiomics on the way!😍
Cycle Hybridization Chain Reaction
14 bp split L+R DNA barcodes
3 color channels
Cellpose-based 3D nucleus segmentation
120 RNA probes + 8 antibodies
~50 µm hippocampal slice
44 imaging cycles over 11 days
@science.org 2025
www.science.org/doi/10.1126/...
Cycle Hybridization Chain Reaction
14 bp split L+R DNA barcodes
3 color channels
Cellpose-based 3D nucleus segmentation
120 RNA probes + 8 antibodies
~50 µm hippocampal slice
44 imaging cycles over 11 days
@science.org 2025
www.science.org/doi/10.1126/...
Save the dates for the upcoming #YMIA python-based event series!
🔧Setting up Conda environments
🧠Intro to #LLMs in Bioimage Analysis
💡 Mastering Prompt Engineering
🔬 Hands-on with Cellpose for image segmentation
Perfect for bioimage enthusiasts & ML beginners! #AI #Bioinformatics #MachineLearning
🔧Setting up Conda environments
🧠Intro to #LLMs in Bioimage Analysis
💡 Mastering Prompt Engineering
🔬 Hands-on with Cellpose for image segmentation
Perfect for bioimage enthusiasts & ML beginners! #AI #Bioinformatics #MachineLearning
September 27, 2024 at 10:50 AM
Save the dates for the upcoming #YMIA python-based event series!
🔧Setting up Conda environments
🧠Intro to #LLMs in Bioimage Analysis
💡 Mastering Prompt Engineering
🔬 Hands-on with Cellpose for image segmentation
Perfect for bioimage enthusiasts & ML beginners! #AI #Bioinformatics #MachineLearning
🔧Setting up Conda environments
🧠Intro to #LLMs in Bioimage Analysis
💡 Mastering Prompt Engineering
🔬 Hands-on with Cellpose for image segmentation
Perfect for bioimage enthusiasts & ML beginners! #AI #Bioinformatics #MachineLearning
Cool, thank you. I was asking because I had problems with Conda and CellPose
March 12, 2025 at 4:22 PM
Cool, thank you. I was asking because I had problems with Conda and CellPose
Followed by a very interesting presentation from Stephan Fisher on the Bioinformatics analysis part of the spatial omics pipeline, and a great improvised session of retraining Cellpose in QuPath using SAM annotation by Thierry Pecot
May 15, 2025 at 3:53 PM
Followed by a very interesting presentation from Stephan Fisher on the Bioinformatics analysis part of the spatial omics pipeline, and a great improvised session of retraining Cellpose in QuPath using SAM annotation by Thierry Pecot
Cellpose-SAM: superhuman generalization for cellular segmentation [new]
Adapts a foundation model to Cellpose, improving generalization by increasing robustness to image distortions, surpassing inter-human agreement.
Adapts a foundation model to Cellpose, improving generalization by increasing robustness to image distortions, surpassing inter-human agreement.
May 1, 2025 at 7:05 PM
Cellpose-SAM: superhuman generalization for cellular segmentation [new]
Adapts a foundation model to Cellpose, improving generalization by increasing robustness to image distortions, surpassing inter-human agreement.
Adapts a foundation model to Cellpose, improving generalization by increasing robustness to image distortions, surpassing inter-human agreement.
Cellpose as a reliable method for single-cell segmentation of autofluorescence microscopy images https://www.biorxiv.org/content/10.1101/2024.06.07.597994v1
Cellpose as a reliable method for single-cell segmentation of autofluorescence microscopy images https://www.biorxiv.org/content/10.1101/2024.06.07.597994v1
Autofluorescence microscopy uses intrinsic sources of molecular contrast to provide cellular-level i
www.biorxiv.org
June 10, 2024 at 4:46 PM
Cellpose as a reliable method for single-cell segmentation of autofluorescence microscopy images https://www.biorxiv.org/content/10.1101/2024.06.07.597994v1
Following general
introduction, we try to understand how the famous CellPose works.
www.nature.com/articles/s41...
introduction, we try to understand how the famous CellPose works.
www.nature.com/articles/s41...
March 20, 2025 at 2:13 PM
Following general
introduction, we try to understand how the famous CellPose works.
www.nature.com/articles/s41...
introduction, we try to understand how the famous CellPose works.
www.nature.com/articles/s41...
Cellpose-SAM is currently available in the GUI.
May 4, 2025 at 2:47 PM
Cellpose-SAM is currently available in the GUI.
Turns out Transformers do outperform Cellpose when trained by Marius and Carsen 😄 Super exiting to see this being released and can't wait to try it out on our data!
🚀🔬🦠 Releasing 🤖Cellpose-SAM🤖, a cellular segmentation algorithm with superhuman generalization 🦸♀️. Try it now on 🤗 huggingface.co/spaces/mouse...
paper: www.biorxiv.org/content/10.1...
w/ @computingnature.bsky.social 1/n
paper: www.biorxiv.org/content/10.1...
w/ @computingnature.bsky.social 1/n
May 5, 2025 at 5:33 PM
Turns out Transformers do outperform Cellpose when trained by Marius and Carsen 😄 Super exiting to see this being released and can't wait to try it out on our data!
🧫Does anyone know of database for 2D plant anatomical data?
I’m especially thinking of datasets from: CellSeT, Icy (.xml) or .zip ImageJ ROIs (e.g., via Celer, PaCeQuant, Cellpose, etc.)
Something like what’s being done with ggPlantMap would be amazing!
#PlantScience #OpenScience
I’m especially thinking of datasets from: CellSeT, Icy (.xml) or .zip ImageJ ROIs (e.g., via Celer, PaCeQuant, Cellpose, etc.)
Something like what’s being done with ggPlantMap would be amazing!
#PlantScience #OpenScience
April 11, 2025 at 8:35 AM
🧫Does anyone know of database for 2D plant anatomical data?
I’m especially thinking of datasets from: CellSeT, Icy (.xml) or .zip ImageJ ROIs (e.g., via Celer, PaCeQuant, Cellpose, etc.)
Something like what’s being done with ggPlantMap would be amazing!
#PlantScience #OpenScience
I’m especially thinking of datasets from: CellSeT, Icy (.xml) or .zip ImageJ ROIs (e.g., via Celer, PaCeQuant, Cellpose, etc.)
Something like what’s being done with ggPlantMap would be amazing!
#PlantScience #OpenScience
evaluation of real-time segmentation methods and a realtime data analysis dashboard. Our autofocusing achieves a Mean Absolute Error of 0.0226\textmu m with inference times below 50~ms. Among eleven Deep Learning segmentation methods, Cellpose~3 [3/4 of https://arxiv.org/abs/2504.00047v1]
April 2, 2025 at 6:16 AM
evaluation of real-time segmentation methods and a realtime data analysis dashboard. Our autofocusing achieves a Mean Absolute Error of 0.0226\textmu m with inference times below 50~ms. Among eleven Deep Learning segmentation methods, Cellpose~3 [3/4 of https://arxiv.org/abs/2504.00047v1]
We took a “no cell shall be left behind” approach which wouldn’t be possible without #Cellpose, #TrackMate by @jytinevez.bsky.social , #Fiji and #rstats analysis and visualization with GlmmTMB, emmeans and #SuperPlots and microscopy cores at UCSD. Plasmids available from @addgene.bsky.social
January 24, 2025 at 6:48 PM
We took a “no cell shall be left behind” approach which wouldn’t be possible without #Cellpose, #TrackMate by @jytinevez.bsky.social , #Fiji and #rstats analysis and visualization with GlmmTMB, emmeans and #SuperPlots and microscopy cores at UCSD. Plasmids available from @addgene.bsky.social
The next day, more exercises, but just after lunch, we were lucky enough to hear a great lecture by Carson Stringer on instance segmentation and CellPose. 👀
October 19, 2023 at 8:30 AM
The next day, more exercises, but just after lunch, we were lucky enough to hear a great lecture by Carson Stringer on instance segmentation and CellPose. 👀