TY - GEN
T1 - Fusion and integration pipelines for optical and chemical imaging data for clinical interpretation in ex-vivo diagnosis
AU - Rafsanjani, Mohd Rifqi
AU - Jirstrom, Karin
AU - Rahman, Arman
AU - Prehn, Jochen H.M.
AU - Gallagher, William
AU - Meade, Aidan D.
N1 - Publisher Copyright:
© 2024 SPIE.
PY - 2024
Y1 - 2024
N2 - In the realm of ex-vivo diagnosis, the integration of optical and chemical imaging data has emerged as a transformative approach, offering a comprehensive understanding of biological specimens at a molecular level. Chemical imaging of human tissue specimens provides an all-digital label-free approach to imaging in objective histopathology, though it requires reference to gold standard pathological (e.g. haematoxylin and eosin (H+E) stained) images for pathological interpretation. Optical imaging techniques, such as microscopy and spectroscopy, provide detailed spatial information, capturing morphological features with high resolution. Concurrently, chemical imaging methods, including mass spectrometry and Raman spectroscopy, offer insights into molecular composition. The challenge lies in harnessing the complementary strengths of these disparate modalities to extract a holistic understanding of the sample. In this work we present the results of several image alignment approaches for fusion and integration of chemical and pathological imaging data, demonstrating that the process of corner detection is crucial towards precise image alignment.
AB - In the realm of ex-vivo diagnosis, the integration of optical and chemical imaging data has emerged as a transformative approach, offering a comprehensive understanding of biological specimens at a molecular level. Chemical imaging of human tissue specimens provides an all-digital label-free approach to imaging in objective histopathology, though it requires reference to gold standard pathological (e.g. haematoxylin and eosin (H+E) stained) images for pathological interpretation. Optical imaging techniques, such as microscopy and spectroscopy, provide detailed spatial information, capturing morphological features with high resolution. Concurrently, chemical imaging methods, including mass spectrometry and Raman spectroscopy, offer insights into molecular composition. The challenge lies in harnessing the complementary strengths of these disparate modalities to extract a holistic understanding of the sample. In this work we present the results of several image alignment approaches for fusion and integration of chemical and pathological imaging data, demonstrating that the process of corner detection is crucial towards precise image alignment.
UR - http://www.scopus.com/inward/record.url?scp=85200258104&partnerID=8YFLogxK
U2 - 10.1117/12.3022269
DO - 10.1117/12.3022269
M3 - Conference contribution
AN - SCOPUS:85200258104
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Data Science for Photonics and Biophotonics
A2 - Bocklitz, Thomas
PB - SPIE
T2 - Data Science for Photonics and Biophotonics 2024
Y2 - 10 April 2024 through 12 April 2024
ER -