python ensemble.py --prob_dir output_from_inference --img_path test_images_path --out_path output_path For UNesT with TICV/PFV estimation, we use inference_ticv.py to test and save the final output into Nifti format. The trained model weight from whole brain segmentation with TICV/PFV...
Transfer Learning from Partial Annotations for Whole Brain Segmentation,程序员大本营,技术文章内容聚合第一站。
We conducted a large-scale whole-brain morphometry study by analyzing 3.7 peta-voxels of mouse brain images at the single-cell resolution, producing one of the largest multi-morphometry databases of mammalian brains to date. We registered 204 mouse brains of three major imaging modalities to the ...
The completion of the first whole-brain connectome of an adult fly, containing over 130,000 neurons and millions of synaptic connections1,2,3, offers an opportunity to analyse the statistical properties and topological features of a complete brain. Here we computed the prevalence of two- and ...
FastSurfer Lesion Inpainting Tool (FastSurfer-LIT) for lesion inpainting e.g. for whole brain segmentation and cortical surface reconstruction in the presence of tumor, surgical cavities or other abnormalities - Deep-MI/LIT
(405-nm channel). The latter two channels were used for cell segmentation as described below. For the second and all following imaging rounds, we collected images in the 750-nm, 650-nm and 560-nm channels for the two readout probes and fiducial beads. During each imaging round, for the...
Whole brain fMRI data were recorded with a volume repetition time of 2 s. For further information on the acquisition parameters, please consult the original work (Henson et al.2002). The data were pre-processed using SPM8. This included motion correction, segmentation, normalization to the MNI...
The first strategy, which involves all the image stacks into a terabyte volume and then perform neuron tracing, synapse segmentation and spatial analysis globally on the combined volume. The downside of the approach is a big data problem of manipulating, storing and analyzing the giant volume. Add...
The colour-based segmentation frequently resulted in the separation of different tissue types within a WSI, such as blood stains from muscles, fat, and in some cases, even cancerous regions. In a second stage of segmentation, a small percentage of patches are randomly selected by preserving the...
(cells, neurons, vessels, etc). Specifically, ImPartial augments the segmentation objective via self-supervised multi-channel quantized imputation. This approach leverages the observation that perfect pixel-wise reconstruction or denoising of the image is not needed for accurate segmentation, and thus, ...