Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis.

Read full text
Authors: Jan Sellner, Alexander Studier‐Fischer, Ahmad Bin Qasim, Silvia Seidlitz, Nicholas Schreck, Minu D. Tizabi, Manuel Wiesenfarth, Annette Kopp-Schneider, Janne Heinecke, J. Brandt, Samuel A. Knoedler, Caelán Max Haney
+7 more Gabriel Alexander Salg, Berkin Özdemir, Maximilian Dietrich, Maurice Stephan Michel, Felix Nickel, Karl‐Friedrich Kowalewski, Lena Maier‐Hein
Cited by: 0

Abstract

This dataset contains semantically annotated spectral data from multiple species and three different perfusion states (physiological, malperfused and ICG). The HSI cubes were acquired with the Tivita® Tissue camera system from Diaspective Vision. Each data cube has the dimensions (480, 640, 100) = (height, width, channels) with the 100 non-overlapping spectral channels being in the range from 500 nm to 1000 nm at a spectral resolution of around 5 nm. This repository contains the raw data, related metadata as well as the preprocessed files. The full dataset is deposited here: https://spectralverse-heidelberg.org/xeno-spectral/

Fields of Study & Subjects

Optical Imaging and Spectroscopy Techniques Spectroscopy Techniques in Biomedical and Chemical Research Remote-Sensing Image Classification

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
26 January 2026
Language
EN
Document type
Dataset