Literature behind MADI3D workflows for volume rendering, stitching, registration and neuron comparison.
Formal MADI3D software papers, preprints and methods notes will be listed here when released. The references below describe methods used or integrated by the application.
Volume rendering
Wan Y, Otsuna H, Chien CB, Hansen C. FluoRender: an application of 2D image space methods for 3D and 4D confocal microscopy data visualization in neurobiology research. BMC Bioinformatics. 2017.
DOI 10.1186/s12859-017-1694-93D microscopy stitching
Preibisch S, Saalfeld S, Tomancak P. Globally optimal stitching of tiled 3D microscopic image acquisitions. Bioinformatics. 2009;25(11):1463–1465.
DOI 10.1093/bioinformatics/btp184Registration
Rohlfing T, Maurer CR Jr. Nonrigid image registration in shared-memory multiprocessor environments with application to brains, breasts, and bees. IEEE Transactions on Information Technology in Biomedicine. 2003.
DOI 10.1109/TITB.2003.808506Original Color-Depth MIP search method
Otsuna H, Ito M, Kawase T. Color depth MIP mask search: a new tool to expedite Split-GAL4 creation. bioRxiv preprint. 2018.
DOI 10.1101/318006 · Original Fiji plugin sourceColor-Depth MIP search
Janelia's open-source Color-Depth MIP search tools use the algorithms of the earlier Fiji ColorMIP Mask Search plugin and produce precomputed results for NeuronBridge.
ColorMIPSearch source codeSearchable light-microscopy image resource
Meissner GW, et al. A searchable image resource of Drosophila GAL4 driver expression patterns with single neuron resolution. eLife. 2023;12:e80660.
DOI 10.7554/eLife.80660LM ↔ EM morphology search
Clements J, et al. NeuronBridge: an intuitive web application for neuronal morphology search across large data sets. BMC Bioinformatics. 2024.
DOI 10.1186/s12859-024-05732-7MADI3D can ingest NeuronBridge Color MIP search results and retrieve associated LM and EM data for direct 3D inspection. The intended sequence is microscopy → registration → segmentation → morphology search → candidate retrieval → high-resolution 3D comparison.
This keeps automated search as a candidate-retrieval stage rather than treating a single similarity score as the final biological decision.
