update lists

html/biologicalimageanalysis.html

@@ -100,6 +100,9 @@ PyTorch-based package for deep/machine learning analysis of microscopy
 data.</li>
 <li><a href="https://github.com/MouseLand/cellpose">Cellpose</a> - A
 generalist algorithm for cell and nucleus segmentation.</li>
+<li><a href="https://github.com/vanvalenlab/cellSAM">CellSAM</a> - A
+foundation model for cell segmentation trained on a diverse range of
+cells and data types.</li>
 <li><a href="https://github.com/Sentinal4D/cellshape">Cellshape</a> - 3D
 single-cell shape analysis of cancer cells using geometric deep
 learning.</li>
@@ -128,11 +131,18 @@ interactively.</li>
 <li><a href="https://github.com/ijpb/MorphoLibJ">MorpholibJ</a> -
 Collection of mathematical morphology methods and plugins for
 ImageJ.</li>
+<li><a href="https://github.com/aelefebv/nellie">Nellie</a> - Automated
+organelle segmentation, tracking, and hierarchical feature extraction in
+2D/3D live-cell microscopy.</li>
 <li><a href="https://github.com/4DNucleome/PartSeg">PartSeg</a> - A GUI
 and a library for segmentation algorithms.</li>
+<li><a href="https://github.com/dcjones/proseg">Proseg</a> : A cell
+segmentation method for in situ spatial transcriptomics.</li>
 <li><a href="https://github.com/Borda/pyImSegm">PyImSegm</a> - Image
 segmentation - general superpixel segmentation and center detection and
 region growing.</li>
+<li><a href="https://github.com/JackieZhai/SALEM2">Salem²</a> - Segment
+Anything in Light and Electron Microscopy via Membrane Guidance.</li>
 <li><a href="https://github.com/scverse/squidpy">Squidpy</a> - Python
 framework that brings together tools from omics and image analysis to
 enable scalable description of spatial molecular data, such as
@@ -322,6 +332,8 @@ way.</li>
 <li><a href="https://github.com/quantixed/TrackMateR">TrackMateR</a> - R
 package to analyze cell migration and particle tracking experiments
 using outputs from TrackMate.</li>
+<li><a href="https://soft-matter.github.io/trackpy">Trackpy</a> - Fast
+and Flexible Particle-Tracking Toolkit.</li>
 <li><a href="https://gitlab.com/csb.ethz/tracx">TracX</a> - MATLAB
 generic toolbox for cell tracking from various microscopy image
 modalities such as Bright-field (BF), phase contrast (PhC) or
@@ -336,6 +348,9 @@ approach (through Renjin).</li>
 <li><a href="https://github.com/CellDynamics/QuimP">QuimP</a> - Software
 for tracking cellular shape changes and dynamic distributions of
 fluorescent reporters at the cell membrane.</li>
+<li><a href="https://github.com/royerlab/ultrack">Ultrack</a> -
+Versatile cell tracking method for 2D, 3D, and multichannel timelapses,
+overcoming segmentation challenges in complex tissues.</li>
 <li><a href="https://github.com/oist/usiigaci">Usiigaci</a> - Stain-free
 cell tracking in phase contrast microscopy enabled by supervised machine
 learning.</li>
@@ -390,6 +405,8 @@ inside large 3-dimensional biofilm communities in space and time.</li>
 <li><a href="https://git.ecdf.ed.ac.uk/swain-lab/baby/">BABY</a> - An
 image processing pipeline for accurate single-cell growth estimation of
 budding cells from bright-field stacks.</li>
+<li><a href="https://github.com/rraadd88/htsimaging">htsimaging</a> -
+Python package for high-throughput single-cell imaging analysis.</li>
 <li><a href="https://yeastmate.readthedocs.io/en/latest/">YeastMate</a>
 - Neural network-assisted segmentation of mating and budding events in
 S. cerevisiae.</li>
@@ -527,3 +544,6 @@ href="https://github.com/HohlbeinLab/OpenMicroscopy">OpenMicroscopy</a>
 - Non-comprehensive list of projects and resources related to open
 microscopy.</li>
 </ul>
+<p><a
+href="https://github.com/hallvaaw/awesome-biological-image-analysis">biologicalimageanalysis.md
+Github</a></p>