In situ histology of mice skin through transfer learning of tissue energy interaction in optical coherence tomography

Debdoot Sheet, Amrita Chaudhary, Sri Phani Krishna Karri, Debnath Das, Amin Katouzian, Provas Banerjee, Nassir Navab, Jyotirmoy Chatterjee, Ajoy K. Ray

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Tissue characterization method in optical coherence tomography (OCT) for in situ histology of soft tissues is presented and demonstrated for mice skin. OCT allows direct noninvasive visualization of subsurface anatomy. It is currently used for in situ investigation of lesions in skin, vessels, retinal layers, oral, and bronchial cavitities. Although OCT images present high resolution information about tissue morphology, reporting requires a reader experienced in interpretation of the images, viz., identification of anatomical layers and structures constituting the organ based on OCT speckle appearance. Our approach characterizes tissues through transfer learning of tissue energy interaction statistical physics models of ballistic and nearballistic photons. The clinical information yield with our approach is comparable to conventional invasive histology. On cross evaluation with a mice model experiment, the epidermis, papillary dermis, dermis, and adipose tissue constituting the mice skin are identified with an accuracy of 99%, 95%, 99%, and 98%, respectively. This high accuracy of characterizing heterogeneous tissues using OCT justifies the ability of our computational approach to perform in situ histology and can be extended to regular clinical practice for diagnosis of vascular, retinal, or oral pathologies.

Original languageEnglish
Article number090503
JournalJournal of Biomedical Optics
Volume18
Issue number9
DOIs
StatePublished - 2013

Keywords

  • Optical coherence tomography
  • in situ histology
  • machine learning
  • statistics of ballistic photon imaging
  • tissue characterization

Fingerprint

Dive into the research topics of 'In situ histology of mice skin through transfer learning of tissue energy interaction in optical coherence tomography'. Together they form a unique fingerprint.

Cite this