Automated diagnosis of colon cancer using hyperspectral sensing

Robert J. Beaulieu, Seth Daniel Goldstein, Jasvinder Singh, Bashar Safar, Amit Banerjee*, Nita Ahuja

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Scopus citations


Background: Surgical management of colorectal cancer relies on accurate identification of tumor and possible metastatic disease. Hyperspectral (HS) sensing is a passive, non-ionizing diagnostic method that has been considered for multiple tumor types. The ability to use HS for identification of tumor specimens during surgical resection of colorectal cancers was explored. Methods: Patients with colorectal cancer who underwent operative resection were enrolled. HS measurements were performed both intra- and extra-luminally. Spectral results were correlated with pathologic evaluation. Results: Fifteen patient specimens were analyzed. For patients with confirmed colorectal cancer, extraluminal spectra analysis yielded 61.68% sensitivity with 90% specificity. For intraluminal specimens, sensitivity increased to 91.97% with 90% specificity. Conclusions: Hyperspectral sensing can reliably detect tumors in resected colon specimens. This research offers promising results for a diagnostic technology that is non-ionizing and does not require the use of contrast agents to achieve accurate colorectal cancer detection.

Original languageEnglish (US)
Article numbere1897
JournalInternational Journal of Medical Robotics and Computer Assisted Surgery
Issue number3
StatePublished - Jun 2018


  • colorectal cancer
  • diagnostics
  • hyperspectral

ASJC Scopus subject areas

  • Surgery
  • Biophysics
  • Computer Science Applications


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