Abstract: This dataset contains Multispectral Mueller matrices of lamb brain. A total of six fresh brain specimens were imaged, mainly in lateral and medial views, but also in sections. The wavelengths used are 450, 500, 550, 590, 650, and 680 nm. The dataset was generated using Python and contains a total of twenty matrices, following this folder structure: -Specimen (1 to 6) View: right or left hemispheres; cerebellum hemispheres; medial or lateral view; sections; frontal basal ganglia (bg) sections; pineal region; brain stem sections. Data in hdf5 (data.h5) format filled with Python objects M: Mueller matrix. Dimensions: (6, 4, 4, 604, 642) corresponding to (wavelength, matrix row, matrix column, pixels row, pixels column). Python's numpy.array followed filled with numpy.float64. ref_img: Reference grayscale image (at 450 nm). Dimensions: (604, 642) corresponding to (pixels row, pixels column). Python's numpy.array followed filled with numpy.float64. roi: Region of interest. Its values are 1 inside the sample and 0 in the background. Dimensions: (604, 642) corresponding to (pixels row, pixels column). Python's numpy.array followed filled with numpy.int32. labels: Labelled areas. There are 14 different white matter and gray matter structures. Dimensions: (604, 642) corresponding to (pixels row, pixels column). wvls: Wavelengths in descending order. Dimensions: (6) corresponding to (wavelengths). Figure representing the data inside data.h5 (data.png). -labels.csv: CSV file containing the legend for the labels. WM and GM stand for white matter and gray matter, respectivelly. This dataset was used in a manuscript currently under peer review (May 2024). Upon publication, the embargo will be removed and we will update the information to provide a more detailed presentation of the dataset.

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